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TDengine
TDengine

taosdata / TDengine
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TDengine
TDengine
提交 3689b41f 编写于 作者: B Benguang Zhao
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Merge branch '3.0' into FIX/TD-24182-3.0

上级 ae26f701 d777e37f
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README-CN.md
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......@@ -15,7 +15,7 @@
[![Coverage Status](https://coveralls.io/repos/github/taosdata/TDengine/badge.svg?branch=develop)](https://coveralls.io/github/taosdata/TDengine?branch=develop)
[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/4201/badge)](https://bestpractices.coreinfrastructure.org/projects/4201)
简体中文 | [English](README.md) | 很多职位正在热招中，请看[这里](https://www.taosdata.com/cn/careers/)
简体中文 | [English](README.md) | [TDengine 云服务](https://cloud.taosdata.com/?utm_medium=cn&utm_source=github) | 很多职位正在热招中，请看[这里](https://www.taosdata.com/cn/careers/)
# TDengine 简介
......@@ -52,7 +52,7 @@ TDengine 还提供一组辅助工具软件 taosTools，目前它包含 taosBench
### Ubuntu 18.04 及以上版本 & Debian：
```bash
sudo apt-get install -y gcc cmake build-essential git libssl-dev libgflags2.2 libgflags-dev
sudo apt-get install -y gcc cmake build-essential git libssl-dev libgflags2.2 libgflags-dev libgeos-dev
```
#### 为 taos-tools 安装编译需要的软件
......@@ -68,14 +68,14 @@ sudo apt install build-essential libjansson-dev libsnappy-dev liblzma-dev libz-d
```bash
sudo yum install epel-release
sudo yum update
sudo yum install -y gcc gcc-c++ make cmake3 git openssl-devel
sudo yum install -y gcc gcc-c++ make cmake3 git openssl-devel geos geos-devel
sudo ln -sf /usr/bin/cmake3 /usr/bin/cmake
```
### CentOS 8 & Fedora
### CentOS 8/Fedora/Rocky Linux
```bash
sudo dnf install -y gcc gcc-c++ make cmake epel-release git openssl-devel
sudo dnf install -y gcc gcc-c++ make cmake epel-release git openssl-devel geos geos-devel
```
#### 在 CentOS 上构建 taosTools 安装依赖软件
......@@ -88,7 +88,7 @@ sudo dnf install -y gcc gcc-c++ make cmake epel-release git openssl-devel
sudo yum install -y zlib-devel zlib-static xz-devel snappy-devel jansson jansson-devel pkgconfig libatomic libatomic-static libstdc++-static openssl-devel
```
#### CentOS 8/Rocky Linux
#### CentOS 8/Fedora/Rocky Linux
```
sudo yum install -y epel-release
......@@ -101,7 +101,7 @@ sudo yum install -y zlib-devel zlib-static xz-devel snappy-devel jansson jansson
若 powertools 安装失败，可以尝试改用：
```
sudo yum config-manager --set-enabled Powertools
sudo yum config-manager --set-enabled powertools
```
#### CentOS + devtoolset
......@@ -117,7 +117,7 @@ scl enable devtoolset-9 -- bash
### macOS
```
brew install argp-standalone pkgconfig
brew install argp-standalone pkgconfig geos
```
### 设置 golang 开发环境
......
README.md
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......@@ -60,7 +60,7 @@ To build TDengine, use [CMake](https://cmake.org/) 3.0.2 or higher versions in t
### Ubuntu 18.04 and above or Debian
```bash
sudo apt-get install -y gcc cmake build-essential git libssl-dev libgflags2.2 libgflags-dev
sudo apt-get install -y gcc cmake build-essential git libssl-dev libgflags2.2 libgflags-dev libgeos-dev
```
#### Install build dependencies for taosTools
......@@ -76,14 +76,14 @@ sudo apt install build-essential libjansson-dev libsnappy-dev liblzma-dev libz-d
```bash
sudo yum install epel-release
sudo yum update
sudo yum install -y gcc gcc-c++ make cmake3 git openssl-devel
sudo yum install -y gcc gcc-c++ make cmake3 git openssl-devel geos geos-devel
sudo ln -sf /usr/bin/cmake3 /usr/bin/cmake
```
### CentOS 8 & Fedora
### CentOS 8/Fedora/Rocky Linux
```bash
sudo dnf install -y gcc gcc-c++ make cmake epel-release git openssl-devel
sudo dnf install -y gcc gcc-c++ make cmake epel-release git openssl-devel geos geos-devel
```
#### Install build dependencies for taosTools on CentOS
......@@ -94,7 +94,7 @@ sudo dnf install -y gcc gcc-c++ make cmake epel-release git openssl-devel
sudo yum install -y zlib-devel zlib-static xz-devel snappy-devel jansson jansson-devel pkgconfig libatomic libatomic-static libstdc++-static openssl-devel
```
#### CentOS 8/Rocky Linux
#### CentOS 8/Fedora/Rocky Linux
```
sudo yum install -y epel-release
......@@ -124,7 +124,7 @@ scl enable devtoolset-9 -- bash
### macOS
```
brew install argp-standalone pkgconfig
brew install argp-standalone pkgconfig geos
```
### Setup golang environment
......
cmake/cmake.define
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......@@ -123,8 +123,8 @@ ELSE ()
SET(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Werror -Werror=return-type -fPIC -O3 -Wformat=2 -Wno-format-nonliteral -Wno-format-truncation -Wno-format-y2k")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Werror -Wno-reserved-user-defined-literal -Wno-literal-suffix -Werror=return-type -fPIC -O3 -Wformat=2 -Wno-format-nonliteral -Wno-format-truncation -Wno-format-y2k")
ELSE ()
SET(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Werror -Werror=return-type -fPIC -gdwarf-2 -g3 -Wformat=2 -Wno-format-nonliteral -Wno-format-truncation -Wno-format-y2k")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-reserved-user-defined-literal -Wno-literal-suffix -Werror=return-type -fPIC -gdwarf-2 -g3 -Wformat=2 -Wno-format-nonliteral -Wno-format-truncation -Wno-format-y2k")
SET(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Werror -Werror=return-type -fPIC -g3 -gdwarf-2 -Wformat=2 -Wno-format-nonliteral -Wno-format-truncation -Wno-format-y2k")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-reserved-user-defined-literal -g3 -Wno-literal-suffix -Werror=return-type -fPIC -gdwarf-2 -Wformat=2 -Wno-format-nonliteral -Wno-format-truncation -Wno-format-y2k")
ENDIF ()
# disable all assert
......
cmake/cmake.options
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......@@ -64,12 +64,25 @@ IF(${TD_WINDOWS})
ON
)
MESSAGE("build geos Win32")
option(
BUILD_GEOS
"If build geos on Windows"
ON
)
ELSEIF (TD_DARWIN_64)
IF(${BUILD_TEST})
add_definitions(-DCOMPILER_SUPPORTS_CXX13)
ENDIF ()
ENDIF ()
option(
BUILD_GEOS
"If build geos on Windows"
ON
)
option(
BUILD_SHARED_LIBS
""
......
cmake/cmake.version
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......@@ -2,7 +2,7 @@
IF (DEFINED VERNUMBER)
SET(TD_VER_NUMBER ${VERNUMBER})
ELSE ()
SET(TD_VER_NUMBER "3.0.4.1")
SET(TD_VER_NUMBER "3.0.5.0")
ENDIF ()
IF (DEFINED VERCOMPATIBLE)
......
cmake/geos_CMakeLists.txt.in 0 → 100644
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# geos
ExternalProject_Add(geos
GIT_REPOSITORY https://github.com/libgeos/geos.git
GIT_TAG 3.11.2
SOURCE_DIR "${TD_CONTRIB_DIR}/geos"
BINARY_DIR ""
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
\ No newline at end of file
cmake/stub_CMakeLists.txt.in
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......@@ -2,6 +2,7 @@
# stub
ExternalProject_Add(stub
GIT_REPOSITORY https://github.com/coolxv/cpp-stub.git
GIT_TAG 5e903b8e
GIT_SUBMODULES "src"
SOURCE_DIR "${TD_CONTRIB_DIR}/cpp-stub"
BINARY_DIR "${TD_CONTRIB_DIR}/cpp-stub/src"
......
cmake/taosadapter_CMakeLists.txt.in
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......@@ -2,7 +2,7 @@
# taosadapter
ExternalProject_Add(taosadapter
GIT_REPOSITORY https://github.com/taosdata/taosadapter.git
GIT_TAG 565ca21
GIT_TAG 3.0
SOURCE_DIR "${TD_SOURCE_DIR}/tools/taosadapter"
BINARY_DIR ""
#BUILD_IN_SOURCE TRUE
......
cmake/taostools_CMakeLists.txt.in
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......@@ -2,7 +2,7 @@
# taos-tools
ExternalProject_Add(taos-tools
GIT_REPOSITORY https://github.com/taosdata/taos-tools.git
GIT_TAG 4378702
GIT_TAG 3.0
SOURCE_DIR "${TD_SOURCE_DIR}/tools/taos-tools"
BINARY_DIR ""
#BUILD_IN_SOURCE TRUE
......
contrib/CMakeLists.txt
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......@@ -134,6 +134,11 @@ if(${BUILD_ADDR2LINE})
endif(NOT ${TD_WINDOWS})
endif(${BUILD_ADDR2LINE})
# geos
if(${BUILD_GEOS})
cat("${TD_SUPPORT_DIR}/geos_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
endif()
# download dependencies
configure_file(${CONTRIB_TMP_FILE} "${TD_CONTRIB_DIR}/deps-download/CMakeLists.txt")
execute_process(COMMAND "${CMAKE_COMMAND}" -G "${CMAKE_GENERATOR}" .
......@@ -226,11 +231,16 @@ if(${BUILD_WITH_ROCKSDB})
if(${TD_LINUX})
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-error=maybe-uninitialized -Wno-error=unused-but-set-variable -Wno-error=unused-variable -Wno-error=unused-function -Wno-errno=unused-private-field -Wno-error=unused-result")
endif(${TD_LINUX})
MESSAGE(STATUS "CXXXX STATUS CONFIG: " ${CMAKE_CXX_FLAGS})
if(${TD_DARWIN})
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-error=maybe-uninitialized")
endif(${TD_DARWIN})
if (${TD_DARWIN_ARM64})
set(HAS_ARMV8_CRC true)
endif(${TD_DARWIN_ARM64})
if (${TD_WINDOWS})
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4244 /wd4819")
endif(${TD_WINDOWS})
......@@ -243,7 +253,7 @@ if(${BUILD_WITH_ROCKSDB})
endif(${TD_DARWIN})
if(${TD_WINDOWS})
option(WITH_JNI "" ON)
option(WITH_JNI "" OFF)
endif(${TD_WINDOWS})
if(${TD_WINDOWS})
......@@ -255,7 +265,7 @@ if(${BUILD_WITH_ROCKSDB})
option(WITH_FALLOCATE "" OFF)
option(WITH_JEMALLOC "" OFF)
option(WITH_GFLAGS "" OFF)
option(PORTABLE "" ON)
option(PORTABLE "" OFF)
option(WITH_LIBURING "" OFF)
option(FAIL_ON_WARNINGS OFF)
......@@ -263,8 +273,11 @@ if(${BUILD_WITH_ROCKSDB})
option(WITH_BENCHMARK_TOOLS "" OFF)
option(WITH_TOOLS "" OFF)
option(WITH_LIBURING "" OFF)
IF (TD_LINUX)
option(ROCKSDB_BUILD_SHARED "Build shared versions of the RocksDB libraries" OFF)
ELSE()
option(ROCKSDB_BUILD_SHARED "Build shared versions of the RocksDB libraries" OFF)
ENDIF()
add_subdirectory(rocksdb EXCLUDE_FROM_ALL)
target_include_directories(
rocksdb
......@@ -470,6 +483,15 @@ if(${BUILD_ADDR2LINE})
endif(NOT ${TD_WINDOWS})
endif(${BUILD_ADDR2LINE})
# geos
if(${BUILD_GEOS})
option(BUILD_SHARED_LIBS "Build GEOS with shared libraries" OFF)
add_subdirectory(geos EXCLUDE_FROM_ALL)
target_include_directories(
geos_c
PUBLIC $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/geos/include>
)
endif(${BUILD_GEOS})
# ================================================================================================
# Build test
......
docs/doxgen/CMakeLists.txt
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......@@ -4,7 +4,7 @@ if(${BUILD_DOCS})
find_package(Doxygen)
if (DOXYGEN_FOUND)
# Build the doc
set(DOXYGEN_IN ${TD_SOURCE_DIR}/docs/Doxyfile.in)
set(DOXYGEN_IN ${TD_SOURCE_DIR}/docs/doxgen/Doxyfile.in)
set(DOXYGEN_OUT ${CMAKE_BINARY_DIR}/Doxyfile)
configure_file(${DOXYGEN_IN} ${DOXYGEN_OUT} @ONLY)
......
docs/en/07-develop/01-connect/index.md
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......@@ -83,7 +83,7 @@ If `maven` is used to manage the projects, what needs to be done is only adding
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>3.0.0</version>
<version>3.2.1</version>
</dependency>
```
......
docs/en/07-develop/07-tmq.mdx
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......@@ -105,6 +105,12 @@ class Consumer:
def poll(self, timeout: float = 1.0):
pass
def assignment(self):
pass
def poll(self, timeout: float = 1.0):
pass
def close(self):
pass
......
docs/en/07-develop/09-udf.md
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此差异已折叠。
docs/en/12-taos-sql/01-data-type.md
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......@@ -42,11 +42,10 @@ In TDengine, the data types below can be used when specifying a column or tag.
| 14 | NCHAR | User Defined | Multi-byte string that can include multi byte characters like Chinese characters. Each character of NCHAR type consumes 4 bytes storage. The string value should be quoted with single quotes. Literal single quote inside the string must be preceded with backslash, like `\'`. The length must be specified when defining a column or tag of NCHAR type, for example nchar(10) means it can store at most 10 characters of nchar type and will consume fixed storage of 40 bytes. An error will be reported if the string value exceeds the length defined. |
| 15 | JSON | | JSON type can only be used on tags. A tag of json type is excluded with any other tags of any other type. |
| 16 | VARCHAR | User-defined | Alias of BINARY |
:::note
- Only ASCII visible characters are suggested to be used in a column or tag of BINARY type. Multi-byte characters must be stored in NCHAR type.
- The length of BINARY can be up to 16,374 bytes. The string value must be quoted with single quotes. You must specify a length in bytes for a BINARY value, for example binary(20) for up to twenty single-byte characters. If the data exceeds the specified length, an error will occur. The literal single quote inside the string must be preceded with back slash like `\'`
- The length of BINARY can be up to 16,374(data column is 65,517 and tag column is 16,382 since version 3.0.5.0) bytes. The string value must be quoted with single quotes. You must specify a length in bytes for a BINARY value, for example binary(20) for up to twenty single-byte characters. If the data exceeds the specified length, an error will occur. The literal single quote inside the string must be preceded with back slash like `\'`
- Numeric values in SQL statements will be determined as integer or float type according to whether there is decimal point or whether scientific notation is used, so attention must be paid to avoid overflow. For example, 9999999999999999999 will be considered as overflow because it exceeds the upper limit of long integer, but 9999999999999999999.0 will be considered as a legal float number.
:::
......
docs/en/12-taos-sql/03-table.md
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......@@ -45,7 +45,7 @@ table_option: {
1. The first column of a table MUST be of type TIMESTAMP. It is automatically set as the primary key.
2. The maximum length of the table name is 192 bytes.
3. The maximum length of each row is 48k bytes, please note that the extra 2 bytes used by each BINARY/NCHAR column are also counted.
3. The maximum length of each row is 48k(64k since version 3.0.5.0) bytes, please note that the extra 2 bytes used by each BINARY/NCHAR column are also counted.
4. The name of the subtable can only consist of characters from the English alphabet, digits and underscore. Table names can't start with a digit. Table names are case insensitive.
5. The maximum length in bytes must be specified when using BINARY or NCHAR types.
6. Escape character "\`" can be used to avoid the conflict between table names and reserved keywords, above rules will be bypassed when using escape character on table names, but the upper limit for the name length is still valid. The table names specified using escape character are case sensitive.
......
docs/en/12-taos-sql/06-select.md
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......@@ -55,7 +55,7 @@ window_clause: {
| INTERVAL(interval_val [, interval_offset]) [SLIDING (sliding_val)] [WATERMARK(watermark_val)] [FILL(fill_mod_and_val)]
interp_clause:
RANGE(ts_val, ts_val) EVERY(every_val) FILL(fill_mod_and_val)
RANGE(ts_val [, ts_val]) EVERY(every_val) FILL(fill_mod_and_val)
partition_by_clause:
PARTITION BY expr [, expr] ...
......
docs/en/12-taos-sql/10-function.md
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......@@ -889,9 +889,10 @@ ignore_null_values: {
- `INTERP` is used to get the value that matches the specified time slice from a column. If no such value exists an interpolation value will be returned based on `FILL` parameter.
- The input data of `INTERP` is the value of the specified column and a `where` clause can be used to filter the original data. If no `where` condition is specified then all original data is the input.
- `INTERP` must be used along with `RANGE`, `EVERY`, `FILL` keywords.
- The output time range of `INTERP` is specified by `RANGE(timestamp1,timestamp2)` parameter, with timestamp1 <= timestamp2. timestamp1 is the starting point of the output time range and must be specified. timestamp2 is the ending point of the output time range and must be specified.
- The output time range of `INTERP` is specified by `RANGE(timestamp1,timestamp2)` parameter, with timestamp1 <= timestamp2. timestamp1 is the starting point of the output time range. timestamp2 is the ending point of the output time range.
- The number of rows in the result set of `INTERP` is determined by the parameter `EVERY(time_unit)`. Starting from timestamp1, one interpolation is performed for every time interval specified `time_unit` parameter. The parameter `time_unit` must be an integer, with no quotes, with a time unit of: a(millisecond)), s(second), m(minute), h(hour), d(day), or w(week). For example, `EVERY(500a)` will interpolate every 500 milliseconds.
- Interpolation is performed based on `FILL` parameter. For more information about FILL clause, see [FILL Clause](../distinguished/#fill-clause).
- When only one timestamp value is specified in `RANGE` clause, `INTERP` is used to generate interpolation at this point in time. In this case, `EVERY` clause can be omitted. For example, SELECT INTERP(col) FROM tb RANGE('2023-01-01 00:00:00') FILL(linear).
- `INTERP` can be applied to supertable by interpolating primary key sorted data of all its childtables. It can also be used with `partition by tbname` when applied to supertable to generate interpolation on each single timeline.
- Pseudocolumn `_irowts` can be used along with `INTERP` to return the timestamps associated with interpolation points(support after version 3.0.2.0).
- Pseudocolumn `_isfilled` can be used along with `INTERP` to indicate whether the results are original records or data points generated by interpolation algorithm(support after version 3.0.3.0).
......@@ -902,7 +903,7 @@ ignore_null_values: {
- We want to downsample every 1 hour and use a linear fill for missing values. Note the order in which the "partition by" clause and the "range", "every" and "fill" parameters are used.
```sql
SELECT _irowts,INTERP(current) FROM test.meters PARTITION BY TBNAME RANGE('2017-07-22 00:00:00','2017-07-24 12:25:00') EVERY(1h) FILL(LINEAR)
SELECT _irowts,INTERP(current) FROM test.meters PARTITION BY TBNAME RANGE('2017-07-22 00:00:00','2017-07-24 12:25:00') EVERY(1h) FILL(LINEAR)
```
### LAST
......@@ -1008,8 +1009,7 @@ SAMPLE(expr, k)
**More explanations**:
This function cannot be used in expression calculation.
- Must be used with `PARTITION BY tbname` when it's used on a STable to force the result on each single timeline
- This function cannot be used in expression calculation.
### TAIL
......@@ -1088,7 +1088,6 @@ CSUM(expr)
- Arithmetic operation can't be performed on the result of `csum` function
- Can only be used with aggregate functions This function can be used with supertables and standard tables.
- Must be used with `PARTITION BY tbname` when it's used on a STable to force the result on each single timeline
### DERIVATIVE
......@@ -1112,7 +1111,6 @@ ignore_negative: {
**More explanation**:
- It can be used together with `PARTITION BY tbname` against a STable.
- It can be used together with a selected column. For example: select \_rowts, DERIVATIVE() from.
### DIFF
......@@ -1175,7 +1173,6 @@ MAVG(expr, k)
- Arithmetic operation can't be performed on the result of `MAVG`.
- Can only be used with data columns, can't be used with tags. - Can't be used with aggregate functions.
- Must be used with `PARTITION BY tbname` when it's used on a STable to force the result on each single timeline
### STATECOUNT
......@@ -1201,7 +1198,6 @@ STATECOUNT(expr, oper, val)
**More explanations**:
- Must be used together with `PARTITION BY tbname` when it's used on a STable to force the result into each single timeline]
- Can't be used with window operation, like interval/state_window/session_window
......@@ -1229,7 +1225,6 @@ STATEDURATION(expr, oper, val, unit)
**More explanations**:
- Must be used together with `PARTITION BY tbname` when it's used on a STable to force the result into each single timeline]
- Can't be used with window operation, like interval/state_window/session_window
......@@ -1247,7 +1242,6 @@ TWA(expr)
**Applicable table types**: standard tables and supertables
- Must be used together with `PARTITION BY tbname` to force the result into each single timeline.
## System Information Functions
......
docs/en/12-taos-sql/19-limit.md
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......@@ -26,7 +26,7 @@ The following characters cannot occur in a password: single quotation marks ('),
- Maximum length of database name is 64 bytes
- Maximum length of table name is 192 bytes, excluding the database name prefix and the separator.
- Maximum length of each data row is 48K bytes. Note that the upper limit includes the extra 2 bytes consumed by each column of BINARY/NCHAR type.
- Maximum length of each data row is 48K(64K since version 3.0.5.0) bytes. Note that the upper limit includes the extra 2 bytes consumed by each column of BINARY/NCHAR type.
- The maximum length of a column name is 64 bytes.
- Maximum number of columns is 4096. There must be at least 2 columns, and the first column must be timestamp.
- The maximum length of a tag name is 64 bytes
......
docs/en/14-reference/03-connector/04-java.mdx
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......@@ -32,25 +32,22 @@ TDengine's JDBC driver implementation is as consistent as possible with the rela
Native connections are supported on the same platforms as the TDengine client driver.
REST connection supports all platforms that can run Java.
## Version support
Please refer to [version support list](/reference/connector#version-support)
## Recent update logs
| taos-jdbcdriver version | major changes |
| :---------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------: |
| 3.2.1 | JDBC REST connection supports schemaless/prepareStatement over WebSocket |
| 3.2.0 | This version has been deprecated |
| 3.1.0 | JDBC REST connection supports subscription over WebSocket |
| 3.0.1 - 3.0.4 | fix the resultSet data is parsed incorrectly sometimes. 3.0.1 is compiled on JDK 11, you are advised to use other version in the JDK 8 environment |
| 3.0.0 | Support for TDengine 3.0 |
| 2.0.42 | fix wasNull interface return value in WebSocket connection |
| 2.0.41 | fix decode method of username and password in REST connection |
| 2.0.39 - 2.0.40 | Add REST connection/request timeout parameters |
| 2.0.38 | JDBC REST connections add bulk pull function |
| 2.0.37 | Support json tags |
| 2.0.36 | Support schemaless writing |
| taos-jdbcdriver version | major changes | TDengine version |
| :---------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------: |
| 3.2.1 | subscription add seek function | 3.0.5.0 or later |
| 3.2.1 | JDBC REST connection supports schemaless/prepareStatement over WebSocket | 3.0.3.0 or later |
| 3.2.0 | This version has been deprecated | - |
| 3.1.0 | JDBC REST connection supports subscription over WebSocket | - |
| 3.0.1 - 3.0.4 | fix the resultSet data is parsed incorrectly sometimes. 3.0.1 is compiled on JDK 11, you are advised to use other version in the JDK 8 environment | - |
| 3.0.0 | Support for TDengine 3.0 | 3.0.0.0 or later |
| 2.0.42 | fix wasNull interface return value in WebSocket connection | - |
| 2.0.41 | fix decode method of username and password in REST connection | - |
| 2.0.39 - 2.0.40 | Add REST connection/request timeout parameters | - |
| 2.0.38 | JDBC REST connections add bulk pull function | - |
| 2.0.37 | Support json tags | - |
| 2.0.36 | Support schemaless writing | - |
**Note**: adding `batchfetch` to the REST connection and setting it to true will enable the WebSocket connection.
......@@ -102,6 +99,8 @@ For specific error codes, please refer to.
| 0x2319 | user is required | The user name information is missing when creating the connection |
| 0x231a | password is required | Password information is missing when creating a connection |
| 0x231c | httpEntity is null, sql: | Execution exception occurred during the REST connection |
| 0x231d | can't create connection with server within | Increase the connection time by adding the httpConnectTimeout parameter, or check the connection to the taos adapter. |
| 0x231e | failed to complete the task within the specified time | Increase the execution time by adding the messageWaitTimeout parameter, or check the connection to the taos adapter. |
| 0x2350 | unknown error | Unknown exception, please return to the developer on github. |
| 0x2352 | Unsupported encoding | An unsupported character encoding set is specified under the native Connection. |
| 0x2353 | internal error of database, please see taoslog for more details | An error occurs when the prepare statement is executed on the native connection. Check the taos log to locate the fault. |
......@@ -117,8 +116,8 @@ For specific error codes, please refer to.
| 0x2376 | failed to set consumer topic, topic name is empty | During data subscription creation, the subscription topic name is empty. Check that the specified topic name is correct. |
| 0x2377 | consumer reference has been destroyed | The subscription data transfer channel has been closed. Please check the connection to TDengine. |
| 0x2378 | consumer create error | Failed to create a data subscription. Check the taos log according to the error message to locate the fault. |
| - | can't create connection with server within | Increase the connection time by adding the httpConnectTimeout parameter, or check the connection to the taos adapter. |
| - | failed to complete the task within the specified time | Increase the execution time by adding the messageWaitTimeout parameter, or check the connection to the taos adapter. |
| 0x2379 | seek offset must not be a negative number | The seek interface parameter cannot be negative. Use the correct parameter |
| 0x237a | vGroup not found in result set | subscription is not bound to the VGroup due to the rebalance mechanism |
- [TDengine Java Connector](https://github.com/taosdata/taos-connector-jdbc/blob/main/src/main/java/com/taosdata/jdbc/TSDBErrorNumbers.java)
<!-- - [TDengine_ERROR_CODE](../error-code) -->
......@@ -169,7 +168,7 @@ Add following dependency in the `pom.xml` file of your Maven project:
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>3.2.1</version>
<version>3.2.2</version>
</dependency>
```
......@@ -913,14 +912,15 @@ public class SchemalessWsTest {
public static void main(String[] args) throws SQLException {
final String url = "jdbc:TAOS-RS://" + host + ":6041/?user=root&password=taosdata&batchfetch=true";
Connection connection = DriverManager.getConnection(url);
init(connection);
SchemalessWriter writer = new SchemalessWriter(connection, "test_ws_schemaless");
writer.write(lineDemo, SchemalessProtocolType.LINE, SchemalessTimestampType.NANO_SECONDS);
writer.write(telnetDemo, SchemalessProtocolType.TELNET, SchemalessTimestampType.MILLI_SECONDS);
writer.write(jsonDemo, SchemalessProtocolType.JSON, SchemalessTimestampType.SECONDS);
System.exit(0);
try(Connection connection = DriverManager.getConnection(url)){
init(connection);
try(SchemalessWriter writer = new SchemalessWriter(connection, "test_ws_schemaless")){
writer.write(lineDemo, SchemalessProtocolType.LINE, SchemalessTimestampType.NANO_SECONDS);
writer.write(telnetDemo, SchemalessProtocolType.TELNET, SchemalessTimestampType.MILLI_SECONDS);
writer.write(jsonDemo, SchemalessProtocolType.JSON, SchemalessTimestampType.SECONDS);
}
}
}
private static void init(Connection connection) throws SQLException {
......@@ -959,6 +959,7 @@ The preceding example uses the SQL statement `select ts, speed from speed_table`
```java
Properties config = new Properties();
config.setProperty("bootstrap.servers", "localhost:6030");
config.setProperty("enable.auto.commit", "true");
config.setProperty("group.id", "group1");
config.setProperty("value.deserializer", "com.taosdata.jdbc.tmq.ConsumerTest.ResultDeserializer");
......@@ -966,12 +967,14 @@ config.setProperty("value.deserializer", "com.taosdata.jdbc.tmq.ConsumerTest.Res
TaosConsumer consumer = new TaosConsumer<>(config);
```
- bootstrap.servers: `ip:port` where the TDengine server is located, or `ip:port` where the taosAdapter is located if WebSocket connection is used.
- enable.auto.commit: Specifies whether to commit automatically.
- group.id: consumer: Specifies the group that the consumer is in.
- value.deserializer: To deserialize the results, you can inherit `com.taosdata.jdbc.tmq.ReferenceDeserializer` and specify the result set bean. You can also inherit `com.taosdata.jdbc.tmq.Deserializer` and perform custom deserialization based on the SQL result set.
- td.connect.type: Specifies the type connect with TDengine, `jni` or `WebSocket`. default is `jni`
- httpConnectTimeout: WebSocket connection timeout in milliseconds, the default value is 5000 ms. It only takes effect when using WebSocket type.
- messageWaitTimeout: socket timeout in milliseconds, the default value is 10000 ms. It only takes effect when using WebSocket type.
- httpPoolSize: Maximum number of concurrent requests on the a connection。It only takes effect when using WebSocket type.
- For more information, see [Consumer Parameters](../../../develop/tmq).
#### Subscribe to consume data
......@@ -988,6 +991,17 @@ while(true) {
`poll` obtains one message each time it is run.
#### Assignment subscription Offset
```
long position(TopicPartition partition) throws SQLException;
Map<TopicPartition, Long> position(String topic) throws SQLException;
Map<TopicPartition, Long> beginningOffsets(String topic) throws SQLException;
Map<TopicPartition, Long> endOffsets(String topic) throws SQLException;
void seek(TopicPartition partition, long offset) throws SQLException;
```
#### Close subscriptions
```java
......@@ -1015,10 +1029,20 @@ public abstract class ConsumerLoop {
public ConsumerLoop() throws SQLException {
Properties config = new Properties();
config.setProperty("td.connect.type", "jni");
config.setProperty("bootstrap.servers", "localhost:6030");
config.setProperty("td.connect.user", "root");
config.setProperty("td.connect.pass", "taosdata");
config.setProperty("auto.offset.reset", "earliest");
config.setProperty("msg.with.table.name", "true");
config.setProperty("enable.auto.commit", "true");
config.setProperty("auto.commit.interval.ms", "1000");
config.setProperty("group.id", "group1");
config.setProperty("client.id", "1");
config.setProperty("value.deserializer", "com.taosdata.jdbc.tmq.ConsumerTest.ConsumerLoop$ResultDeserializer");
config.setProperty("value.deserializer.encoding", "UTF-8");
config.setProperty("experimental.snapshot.enable", "true");
this.consumer = new TaosConsumer<>(config);
this.topics = Collections.singletonList("topic_speed");
......@@ -1090,12 +1114,19 @@ public abstract class ConsumerLoop {
public ConsumerLoop() throws SQLException {
Properties config = new Properties();
config.setProperty("bootstrap.servers", "localhost:6041");
config.setProperty("td.connect.type", "ws");
config.setProperty("bootstrap.servers", "localhost:6041");
config.setProperty("td.connect.user", "root");
config.setProperty("td.connect.pass", "taosdata");
config.setProperty("auto.offset.reset", "earliest");
config.setProperty("msg.with.table.name", "true");
config.setProperty("enable.auto.commit", "true");
config.setProperty("auto.commit.interval.ms", "1000");
config.setProperty("group.id", "group2");
config.setProperty("client.id", "1");
config.setProperty("value.deserializer", "com.taosdata.jdbc.tmq.ConsumerTest.ConsumerLoop$ResultDeserializer");
config.setProperty("value.deserializer.encoding", "UTF-8");
config.setProperty("experimental.snapshot.enable", "true");
this.consumer = new TaosConsumer<>(config);
this.topics = Collections.singletonList("topic_speed");
......@@ -1236,6 +1267,7 @@ The source code of the sample application is under `TDengine/examples/JDBC`:
- connectionPools: using taos-jdbcdriver in connection pools such as HikariCP, Druid, dbcp, c3p0, etc.
- SpringJdbcTemplate: using taos-jdbcdriver in Spring JdbcTemplate.
- mybatisplus-demo: using taos-jdbcdriver in Springboot + Mybatis.
- consumer-demo: consumer TDengine data example, the consumption rate can be controlled by parameters.
[JDBC example](https://github.com/taosdata/TDengine/tree/3.0/examples/JDBC)
......
docs/en/14-reference/03-connector/05-go.mdx
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......@@ -29,7 +29,7 @@ REST connections are supported on all platforms that can run Go.
## Version support
Please refer to [version support list](/reference/connector#version-support)
Please refer to [version support list](https://github.com/taosdata/driver-go#remind)
## Supported features
......@@ -379,6 +379,15 @@ Note: `tmq.TopicPartition` is reserved for compatibility purpose
Commit information.
* `func (c *Consumer) Assignment() (partitions []tmq.TopicPartition, err error)`
Get Assignment(TDengine >= 3.0.5.0 and driver-go >= v3.5.0 are required).
* `func (c *Consumer) Seek(partition tmq.TopicPartition, ignoredTimeoutMs int) error`
Note: `ignoredTimeoutMs` is reserved for compatibility purpose
Seek offset(TDengine >= 3.0.5.0 and driver-go >= v3.5.0 are required).
* `func (c *Consumer) Unsubscribe() error`
Unsubscribe.
......@@ -468,6 +477,15 @@ Note: `tmq.TopicPartition` is reserved for compatibility purpose
Commit information.
* `func (c *Consumer) Assignment() (partitions []tmq.TopicPartition, err error)`
Get Assignment(TDengine >= 3.0.5.0 and driver-go >= v3.5.0 are required).
* `func (c *Consumer) Seek(partition tmq.TopicPartition, ignoredTimeoutMs int) error`
Note: `ignoredTimeoutMs` is reserved for compatibility purpose
Seek offset(TDengine >= 3.0.5.0 and driver-go >= v3.5.0 are required).
* `func (c *Consumer) Unsubscribe() error`
Unsubscribe.
......@@ -476,7 +494,7 @@ Unsubscribe.
Close consumer.
For a complete example see [GitHub sample file](https://github.com/taosdata/driver-go/blob/3.0/examples/tmqoverws/main.go)
For a complete example see [GitHub sample file](https://github.com/taosdata/driver-go/blob/main/examples/tmqoverws/main.go)
### parameter binding via WebSocket
......@@ -524,7 +542,7 @@ For a complete example see [GitHub sample file](https://github.com/taosdata/driv
Closes the parameter binding.
For a complete example see [GitHub sample file](https://github.com/taosdata/driver-go/blob/3.0/examples/stmtoverws/main.go)
For a complete example see [GitHub sample file](https://github.com/taosdata/driver-go/blob/main/examples/stmtoverws/main.go)
## API Reference
......
docs/en/14-reference/03-connector/06-rust.mdx
浏览文件 @ 3689b41f
......@@ -27,9 +27,14 @@ The source code for the Rust connectors is located on [GitHub](https://github.co
Native connections are supported on the same platforms as the TDengine client driver.
Websocket connections are supported on all platforms that can run Go.
## Version support
## Version history
Please refer to [version support list](/reference/connector#version-support)
| connector-rust version | TDengine version | major features |
| :----------------: | :--------------: | :--------------------------------------------------: |
| v0.8.10 | 3.0.5.0 or later | TMQ: Get consuming progress and seek offset to consume. |
| v0.8.0 | 3.0.4.0 | Support schemaless insert. |
| v0.7.6 | 3.0.3.0 | Support req_id in query. |
| v0.6.0 | 3.0.0.0 | Base features. |
The Rust Connector is still under rapid development and is not guaranteed to be backward compatible before 1.0. We recommend using TDengine version 3.0 or higher to avoid known issues.
......@@ -499,6 +504,22 @@ The TMQ is of [futures::Stream](https://docs.rs/futures/latest/futures/stream/in
}
```
Get assignments：
Version requirements connector-rust >= v0.8.8, TDengine >= 3.0.5.0
```rust
let assignments = consumer.assignments().await.unwrap();
```
Seek offset：
Version requirements connector-rust >= v0.8.8, TDengine >= 3.0.5.0
```rust
consumer.offset_seek(topic, vgroup_id, offset).await;
```
Unsubscribe:
```rust
......@@ -513,7 +534,7 @@ The following parameters can be configured for the TMQ DSN. Only `group.id` is m
- `enable.auto.commit`: Automatically commits. This can be enabled when data consistency is not essential.
- `auto.commit.interval.ms`: Interval for automatic commits.
For more information, see [GitHub sample file](https://github.com/taosdata/taos-connector-rust/blob/main/examples/subscribe.rs).
For more information, see [GitHub sample file](https://github.com/taosdata/TDengine/blob/3.0/docs/examples/rust/nativeexample/examples/subscribe_demo.rs).
For information about other structure APIs, see the [Rust documentation](https://docs.rs/taos).
......
docs/en/14-reference/03-connector/07-python.mdx
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......@@ -362,7 +362,7 @@ By using the optional req_id parameter, you can specify a request ID that can be
##### TaosConnection class
The `TaosConnection` class contains both an implementation of the PEP249 Connection interface (e.g., the `cursor()` method and the `close()` method) and many extensions (e.g., the `execute()`, `query()`, `schemaless_insert()`, and `subscribe()` methods).
As the way to connect introduced above but add `req_id` argument.
```python title="execute method"
{{#include docs/examples/python/connection_usage_native_reference_with_req_id.py:insert}}
......@@ -372,13 +372,9 @@ The `TaosConnection` class contains both an implementation of the PEP249 Connect
{{#include docs/examples/python/connection_usage_native_reference_with_req_id.py:query}}
```
:::tip
The queried results can only be fetched once. For example, only one of `fetch_all()` and `fetch_all_into_dict()` can be used in the example above. Repeated fetches will result in an empty list.
:::
##### Use of TaosResult class
In the above example of using the `TaosConnection` class, we have shown two ways to get the result of a query: `fetch_all()` and `fetch_all_into_dict()`. In addition, `TaosResult` also provides methods to iterate through the result set by rows (`rows_iter`) or by data blocks (`blocks_iter`). Using these two methods will be more efficient in scenarios where the query has a large amount of data.
As the way to fetch data introduced above but add `req_id` argument.
```python title="blocks_iter method"
{{#include docs/examples/python/result_set_with_req_id_examples.py}}
......@@ -391,17 +387,12 @@ The `TaosConnection` class and the `TaosResult` class already implement all the
{{#include docs/examples/python/cursor_usage_native_reference_with_req_id.py}}
```
:::note
The TaosCursor class uses native connections for write and query operations. In a client-side multi-threaded scenario, this cursor instance must remain thread exclusive and cannot be shared across threads for use, otherwise, it will result in errors in the returned results.
:::
</TabItem>
<TabItem value="rest" label="REST connection">
##### Use of TaosRestCursor class
The `TaosRestCursor` class is an implementation of the PEP249 Cursor interface.
As the way to connect introduced above but add `req_id` argument.
```python title="Use of TaosRestCursor"
{{#include docs/examples/python/connect_rest_with_req_id_examples.py:basic}}
......@@ -421,8 +412,11 @@ The `RestClient` class is a direct wrapper for the [REST API](/reference/rest-ap
For a more detailed description of the `sql()` method, please refer to [RestClient](https://docs.taosdata.com/api/taospy/taosrest/restclient.html).
</TabItem>
<TabItem value="websocket" label="WebSocket connection">
As the way to connect introduced above but add `req_id` argument.
```python
{{#include docs/examples/python/connect_websocket_with_req_id_examples.py:basic}}
```
......@@ -459,6 +453,170 @@ For a more detailed description of the `sql()` method, please refer to [RestClie
</TabItem>
</Tabs>
### Subscription
Connector support data subscription. For more information about subscroption, please refer to [Data Subscription](../../../develop/tmq/).
<Tabs defaultValue="native">
<TabItem value="native" label="native connection">
The `consumer` in the connector contains the subscription api.
#### Create Consumer
The syntax for creating a consumer is `consumer = Consumer(configs)`. For more subscription api parameters, please refer to [Data Subscription](../../../develop/tmq/).
```python
from taos.tmq import Consumer
consumer = Consumer({"group.id": "local", "td.connect.ip": "127.0.0.1"})
```
#### Subscribe topics
The `subscribe` function is used to subscribe to a list of topics.
```python
consumer.subscribe(['topic1', 'topic2'])
```
#### Consume
The `poll` function is used to consume data in tmq. The parameter of the `poll` function is a value of type float representing the timeout in seconds. It returns a `Message` before timing out, or `None` on timing out. You have to handle error messages in response data.
```python
while True:
res = consumer.poll(1)
if not res:
continue
err = res.error()
if err is not None:
raise err
val = res.value()
for block in val:
print(block.fetchall())
```
#### assignment
The `assignment` function is used to get the assignment of the topic.
```python
assignments = consumer.assignment()
```
#### Seek
The `seek` function is used to reset the assignment of the topic.
```python
tp = TopicPartition(topic='topic1', partition=0, offset=0)
consumer.seek(tp)
```
#### After consuming data
You should unsubscribe to the topics and close the consumer after consuming.
```python
consumer.unsubscribe()
consumer.close()
```
#### Tmq subscription example
```python
{{#include docs/examples/python/tmq_example.py}}
```
#### assignment and seek example
```python
{{#include docs/examples/python/tmq_assignment_example.py:taos_get_assignment_and_seek_demo}}
```
</TabItem>
<TabItem value="websocket" label="WebSocket connection">
In addition to native connections, the connector also supports subscriptions via websockets.
#### Create Consumer
The syntax for creating a consumer is "consumer = consumer = Consumer(conf=configs)". You need to specify that the `td.connect.websocket.scheme` parameter is set to "ws" in the configuration. For more subscription api parameters, please refer to [Data Subscription](../../../develop/tmq/#create-a-consumer).
```python
import taosws
consumer = taosws.(conf={"group.id": "local", "td.connect.websocket.scheme": "ws"})
```
#### subscribe topics
The `subscribe` function is used to subscribe to a list of topics.
```python
consumer.subscribe(['topic1', 'topic2'])
```
#### Consume
The `poll` function is used to consume data in tmq. The parameter of the `poll` function is a value of type float representing the timeout in seconds. It returns a `Message` before timing out, or `None` on timing out. You have to handle error messages in response data.
```python
while True:
res = consumer.poll(timeout=1.0)
if not res:
continue
err = res.error()
if err is not None:
raise err
for block in message:
for row in block:
print(row)
```
#### assignment
The `assignment` function is used to get the assignment of the topic.
```python
assignments = consumer.assignment()
```
#### Seek
The `seek` function is used to reset the assignment of the topic.
```python
consumer.seek(topic='topic1', partition=0, offset=0)
```
#### After consuming data
You should unsubscribe to the topics and close the consumer after consuming.
```python
consumer.unsubscribe()
consumer.close()
```
#### Subscription example
```python
{{#include docs/examples/python/tmq_websocket_example.py}}
```
#### Assignment and seek example
```python
{{#include docs/examples/python/tmq_websocket_assgnment_example.py:taosws_get_assignment_and_seek_demo}}
```
</TabItem>
</Tabs>
### Schemaless Insert
Connector support schemaless insert.
......@@ -513,7 +671,8 @@ Insert with req_id argument
| Example program links | Example program content |
| ------------------------------------------------------------------------------------------------------------- | ------------------- ---- |
| [bind_multi.py](https://github.com/taosdata/taos-connector-python/blob/main/examples/bind-multi.py) | parameter binding, bind multiple rows at once |
| [bind_multi.py](https://github.com/taosdata/taos-connector-python/blob/main/examples/bind-multi.py) | parameter binding,
bind multiple rows at once |
| [bind_row.py](https://github.com/taosdata/taos-connector-python/blob/main/examples/bind-row.py) | bind_row.py
| [insert_lines.py](https://github.com/taosdata/taos-connector-python/blob/main/examples/insert-lines.py) | InfluxDB line protocol writing |
| [json_tag.py](https://github.com/taosdata/taos-connector-python/blob/main/examples/json-tag.py) | Use JSON type tags |
......
docs/en/14-reference/03-connector/index.mdx
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......@@ -62,7 +62,7 @@ The different database framework specifications for various programming language
| **Regular Query** | Support | Support | Support | Support | Support | Support |
| **Parameter Binding** | Not Supported | Not Supported | Support | Support | Not Supported | Support |
| **Subscription (TMQ) ** | Supported | Support | Support | Not Supported | Not Supported | Support |
| **Schemaless** | Supported | Not Supported | Not Supported | Not Supported | Not Supported | Not Supported |
| **Schemaless** | Not Supported | Not Supported | Not Supported | Not Supported | Not Supported | Not Supported |
| **Bulk Pulling (based on WebSocket) ** | Support | Support | Support | Support | Support | Support |
| **DataFrame** | Not Supported | Support | Not Supported | Not Supported | Not Supported | Not Supported |
......
docs/en/14-reference/12-config/index.md
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......@@ -111,7 +111,7 @@ The parameters described in this document by the effect that they have on the sy
| Attribute | Description |
| ------------- | ---------------------------------------------- |
| Applicable | Client/Server |
| Meaning | The maximum waiting time to get avaliable conn |
| Meaning | The maximum waiting time to get available conn |
| Value Range | 10-50000000(ms) |
| Default Value | 500000 |
......
docs/en/14-reference/13-schemaless/13-schemaless.md
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......@@ -90,7 +90,7 @@ You can configure smlChildTableName in taos.cfg to specify table names, for exam
Note: TDengine 3.0.3.0 and later automatically detect whether order is consistent. This parameter is no longer used.
:::tip
All processing logic of schemaless will still follow TDengine's underlying restrictions on data structures, such as the total length of each row of data cannot exceed 48 KB and the total length of a tag value cannot exceed 16 KB. See [TDengine SQL Boundary Limits](/taos-sql/limit) for specific constraints in this area.
All processing logic of schemaless will still follow TDengine's underlying restrictions on data structures, such as the total length of each row of data cannot exceed 48 KB(64 KB since version 3.0.5.0) and the total length of a tag value cannot exceed 16 KB. See [TDengine SQL Boundary Limits](/taos-sql/limit) for specific constraints in this area.
:::
## Time resolution recognition
......
docs/en/20-third-party/11-kafka.md
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......@@ -16,165 +16,79 @@ TDengine Source Connector is used to read data from TDengine in real-time and se
![TDengine Database Kafka Connector -- streaming integration with kafka connect](kafka/streaming-integration-with-kafka-connect.webp)
## What is Confluent?
[Confluent](https://www.confluent.io/) adds many extensions to Kafka. include:
1. Schema Registry
2. REST Proxy
3. Non-Java Clients
4. Many packaged Kafka Connect plugins
5. GUI for managing and monitoring Kafka - Confluent Control Center
Some of these extensions are available in the community version of Confluent. Some are only available in the enterprise version.
![TDengine Database Kafka Connector -- Confluent platform](kafka/confluentPlatform.webp)
Confluent Enterprise Edition provides the `confluent` command-line tool to manage various components.
## Prerequisites
1. Linux operating system
2. Java 8 and Maven installed
3. Git is installed
3. Git/curl/vi is installed
4. TDengine is installed and started. If not, please refer to [Installation and Uninstallation](/operation/pkg-install)
## Install Confluent
Confluent provides two installation methods: Docker and binary packages. This article only introduces binary package installation.
## Install Kafka
Execute in any directory:
````
curl -O http://packages.confluent.io/archive/7.1/confluent-7.1.1.tar.gz
tar xzf confluent-7.1.1.tar.gz -C /opt/
curl -O https://downloads.apache.org/kafka/3.4.0/kafka_2.13-3.4.0.tgz
tar xzf kafka_2.13-3.4.0.tgz -C /opt/
ln -s /opt/kafka_2.13-3.4.0 /opt/kafka
````
Then you need to add the `$CONFLUENT_HOME/bin` directory to the PATH.
Then you need to add the `$KAFKA_HOME/bin` directory to the PATH.
```title=".profile"
export CONFLUENT_HOME=/opt/confluent-7.1.1
export PATH=$CONFLUENT_HOME/bin:$PATH
export KAFKA_HOME=/opt/kafka
export PATH=$PATH:$KAFKA_HOME/bin
```
Users can append the above script to the current user's profile file (~/.profile or ~/.bash_profile)
After the installation is complete, you can enter `confluent version` for simple verification:
```
# confluent version
confluent - Confluent CLI
Version: v2.6.1
Git Ref: 6d920590
Build Date: 2022-02-18T06:14:21Z
Go Version: go1.17.6 (linux/amd64)
Development: false
```
## Install TDengine Connector plugin
### Install from source code
```
```shell
git clone --branch 3.0 https://github.com/taosdata/kafka-connect-tdengine.git
cd kafka-connect-tdengine
mvn clean package
unzip -d $CONFLUENT_HOME/share/java/ target/components/packages/taosdata-kafka-connect-tdengine-*.zip
mvn clean package -Dmaven.test.skip=true
unzip -d $KAFKA_HOME/components/ target/components/packages/taosdata-kafka-connect-tdengine-*.zip
```
The above script first clones the project source code and then compiles and packages it with Maven. After the package is complete, the zip package of the plugin is generated in the `target/components/packages/` directory. Unzip this zip package to plugin path. We used `$CONFLUENT_HOME/share/java/` above because it's a build in plugin path.
### Install with confluent-hub
The above script first clones the project source code and then compiles and packages it with Maven. After the package is complete, the zip package of the plugin is generated in the `target/components/packages/` directory. Unzip this zip package to plugin path. We used `$KAFKA_HOME/components/` above because it's a build in plugin path.
[Confluent Hub](https://www.confluent.io/hub) provides a service to download Kafka Connect plugins. After TDengine Kafka Connector is published to Confluent Hub, it can be installed using the command tool `confluent-hub`.
**TDengine Kafka Connector is currently not officially released and cannot be installed in this way**.
### Add configuration file
## Start Confluent
add kafka-connect-tdengine plugin path to `plugin.path` in `$KAFKA_HOME/config/connect-distributed.properties`.
```
confluent local services start
```properties
plugin.path=/usr/share/java,/opt/kafka/components
```
:::note
Be sure to install the plugin before starting Confluent. Otherwise, Kafka Connect will fail to discover the plugins.
:::
## Start Kafka Services
:::tip
If a component fails to start, try clearing the data and restarting. The data directory will be printed to the console at startup, e.g.:
```title="Console output log" {1}
Using CONFLUENT_CURRENT: /tmp/confluent.106668
Starting ZooKeeper
ZooKeeper is [UP]
Starting Kafka
Kafka is [UP]
Starting Schema Registry
Schema Registry is [UP]
Starting Kafka REST
Kafka REST is [UP]
Starting Connect
Connect is [UP]
Starting ksqlDB Server
ksqlDB Server is [UP]
Starting Control Center
Control Center is [UP]
```
Use command bellow to start all services:
To clear data, execute `rm -rf /tmp/confluent.106668`.
:::
```shell
zookeeper-server-start.sh -daemon $KAFKA_HOME/config/zookeeper.properties
### Check Confluent Services Status
kafka-server-start.sh -daemon $KAFKA_HOME/config/server.properties
Use command bellow to check the status of all service:
connect-distributed.sh -daemon $KAFKA_HOME/config/connect-distributed.properties
```
confluent local services status
```
The expected output is:
```
Connect is [UP]
Control Center is [UP]
Kafka is [UP]
Kafka REST is [UP]
ksqlDB Server is [UP]
Schema Registry is [UP]
ZooKeeper is [UP]
```
### Check Successfully Loaded Plugin
After Kafka Connect was completely started, you can use bellow command to check if our plugins are installed successfully:
```
confluent local services connect plugin list
```
The output should contains `TDengineSinkConnector` and `TDengineSourceConnector` as bellow:
```
Available Connect Plugins:
[
{
"class": "com.taosdata.kafka.connect.sink.TDengineSinkConnector",
"type": "sink",
"version": "1.0.0"
},
{
"class": "com.taosdata.kafka.connect.source.TDengineSourceConnector",
"type": "source",
"version": "1.0.0"
},
......
```shell
curl http://localhost:8083/connectors
```
If not, please check the log file of Kafka Connect. To view the log file path, please execute:
The output as bellow:
```txt
[]
```
echo `cat /tmp/confluent.current`/connect/connect.stdout
```
It should produce a path like:`/tmp/confluent.104086/connect/connect.stdout`
Besides log file `connect.stdout` there is a file named `connect.properties`. At the end of this file you can see the effective `plugin.path` which is a series of paths joined by comma. If Kafka Connect not found our plugins, it's probably because the installed path is not included in `plugin.path`.
## The use of TDengine Sink Connector
......@@ -184,40 +98,47 @@ TDengine Sink Connector internally uses TDengine [modeless write interface](/ref
The following example synchronizes the data of the topic meters to the target database power. The data format is the InfluxDB Line protocol format.
### Add configuration file
### Add Sink Connector configuration file
```
```shell
mkdir ~/test
cd ~/test
vi sink-demo.properties
vi sink-demo.json
```
sink-demo.properties' content is following:
```ini title="sink-demo.properties"
name=TDengineSinkConnector
connector.class=com.taosdata.kafka.connect.sink.TDengineSinkConnector
tasks.max=1
topics=meters
connection.url=jdbc:TAOS://127.0.0.1:6030
connection.user=root
connection.password=taosdata
connection.database=power
db.schemaless=line
data.precision=ns
key.converter=org.apache.kafka.connect.storage.StringConverter
value.converter=org.apache.kafka.connect.storage.StringConverter
sink-demo.json' content is following:
```json title="sink-demo.json"
{
"name": "TDengineSinkConnector",
"config": {
"connector.class":"com.taosdata.kafka.connect.sink.TDengineSinkConnector",
"tasks.max": "1",
"topics": "meters",
"connection.url": "jdbc:TAOS://127.0.0.1:6030",
"connection.user": "root",
"connection.password": "taosdata",
"connection.database": "power",
"db.schemaless": "line",
"data.precision": "ns",
"key.converter": "org.apache.kafka.connect.storage.StringConverter",
"value.converter": "org.apache.kafka.connect.storage.StringConverter",
"errors.tolerance": "all",
"errors.deadletterqueue.topic.name": "dead_letter_topic",
"errors.deadletterqueue.topic.replication.factor": 1
}
}
```
Key configuration instructions:
1. `topics=meters` and `connection.database=power` means to subscribe to the data of the topic meters and write to the database power.
2. `db.schemaless=line` means the data in the InfluxDB Line protocol format.
1. `"topics": "meters"` and `"connection.database": "power"` means to subscribe to the data of the topic meters and write to the database power.
2. `"db.schemaless": "line"` means the data in the InfluxDB Line protocol format.
### Create Connector instance
### Create Sink Connector instance
````
confluent local services connect connector load TDengineSinkConnector --config ./sink-demo.properties
````shell
curl -X POST -d @sink-demo.json http://localhost:8083/connectors -H "Content-Type: application/json"
````
If the above command is executed successfully, the output is as follows:
......@@ -237,7 +158,10 @@ If the above command is executed successfully, the output is as follows:
"tasks.max": "1",
"topics": "meters",
"value.converter": "org.apache.kafka.connect.storage.StringConverter",
"name": "TDengineSinkConnector"
"name": "TDengineSinkConnector",
"errors.tolerance": "all",
"errors.deadletterqueue.topic.name": "dead_letter_topic",
"errors.deadletterqueue.topic.replication.factor": "1",
},
"tasks": [],
"type": "sink"
......@@ -258,7 +182,7 @@ meters,location=California.LoSangeles,groupid=3 current=11.3,voltage=221,phase=0
Use kafka-console-producer to write test data to the topic `meters`.
```
cat test-data.txt | kafka-console-producer --broker-list localhost:9092 --topic meters
cat test-data.txt | kafka-console-producer.sh --broker-list localhost:9092 --topic meters
```
:::note
......@@ -269,12 +193,12 @@ TDengine Sink Connector will automatically create the database if the target dat
Use the TDengine CLI to verify that the sync was successful.
```
```sql
taos> use power;
Database changed.
taos> select * from meters;
ts | current | voltage | phase | groupid | location |
_ts | current | voltage | phase | groupid | location |
===============================================================================================================================================================
2022-03-28 09:56:51.249000000 | 11.800000000 | 221.000000000 | 0.280000000 | 2 | California.LosAngeles |
2022-03-28 09:56:51.250000000 | 13.400000000 | 223.000000000 | 0.290000000 | 2 | California.LosAngeles |
......@@ -293,29 +217,36 @@ TDengine Source Connector will convert the data in TDengine data table into [Inf
The following sample program synchronizes the data in the database test to the topic tdengine-source-test.
### Add configuration file
### Add Source Connector configuration file
```
vi source-demo.properties
```shell
vi source-demo.json
```
Input following content:
```ini title="source-demo.properties"
name=TDengineSourceConnector
connector.class=com.taosdata.kafka.connect.source.TDengineSourceConnector
tasks.max=1
connection.url=jdbc:TAOS://127.0.0.1:6030
connection.username=root
connection.password=taosdata
connection.database=test
connection.attempts=3
connection.backoff.ms=5000
topic.prefix=tdengine-source-
poll.interval.ms=1000
fetch.max.rows=100
key.converter=org.apache.kafka.connect.storage.StringConverter
value.converter=org.apache.kafka.connect.storage.StringConverter
```json title="source-demo.json"
{
"name":"TDengineSourceConnector",
"config":{
"connector.class": "com.taosdata.kafka.connect.source.TDengineSourceConnector",
"tasks.max": 1,
"connection.url": "jdbc:TAOS://127.0.0.1:6030",
"connection.username": "root",
"connection.password": "taosdata",
"connection.database": "test",
"connection.attempts": 3,
"connection.backoff.ms": 5000,
"topic.prefix": "tdengine-source",
"poll.interval.ms": 1000,
"fetch.max.rows": 100,
"topic.per.stable": true,
"topic.ignore.db": false,
"out.format": "line",
"key.converter": "org.apache.kafka.connect.storage.StringConverter",
"value.converter": "org.apache.kafka.connect.storage.StringConverter"
}
}
```
### Prepare test data
......@@ -340,40 +271,40 @@ INSERT INTO d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-1
Use TDengine CLI to execute SQL script
```
```shell
taos -f prepare-source-data.sql
```
### Create Connector instance
````
confluent local services connect connector load TDengineSourceConnector --config source-demo.properties
````
```shell
curl -X POST -d @source-demo.json http://localhost:8083/connectors -H "Content-Type: application/json"
```
### View topic data
Use the kafka-console-consumer command-line tool to monitor data in the topic tdengine-source-test. In the beginning, all historical data will be output. After inserting two new data into TDengine, kafka-console-consumer immediately outputs the two new data. The output is in InfluxDB line protocol format.
````
kafka-console-consumer --bootstrap-server localhost:9092 --from-beginning --topic tdengine-source-test
````shell
kafka-console-consumer.sh --bootstrap-server localhost:9092 --from-beginning --topic tdengine-source-test-meters
````
output:
````
```txt
......
meters,location="California.SanFrancisco",groupid=2i32 current=10.3f32,voltage=219i32,phase=0.31f32 1538548685000000000
meters,location="California.SanFrancisco",groupid=2i32 current=12.6f32,voltage=218i32,phase=0.33f32 1538548695000000000
......
````
```
All historical data is displayed. Switch to the TDengine CLI and insert two new pieces of data:
````
```sql
USE test;
INSERT INTO d1001 VALUES (now, 13.3, 229, 0.38);
INSERT INTO d1002 VALUES (now, 16.3, 233, 0.22);
````
```
Switch back to kafka-console-consumer, and the command line window has printed out the two pieces of data just inserted.
......@@ -383,16 +314,16 @@ After testing, use the unload command to stop the loaded connector.
View currently active connectors:
````
confluent local services connect connector status
````
```shell
curl http://localhost:8083/connectors
```
You should now have two active connectors if you followed the previous steps. Use the following command to unload:
````
confluent local services connect connector unload TDengineSinkConnector
confluent local services connect connector unload TDengineSourceConnector
````
```shell
curl -X DELETE http://localhost:8083/connectors/TDengineSinkConnector
curl -X DELETE http://localhost:8083/connectors/TDengineSourceConnector
```
## Configuration reference
......@@ -427,22 +358,19 @@ The following configuration items apply to TDengine Sink Connector and TDengine
3. `timestamp.initial`: Data synchronization start time. The format is 'yyyy-MM-dd HH:mm:ss'. If it is not set, the data importing to Kafka will be started from the first/oldest row in the database.
4. `poll.interval.ms`: The time interval for checking newly created tables or removed tables, default value is 1000.
5. `fetch.max.rows`: The maximum number of rows retrieved when retrieving the database, default is 100.
6. `query.interval.ms`: The time range of reading data from TDengine each time, its unit is millisecond. It should be adjusted according to the data flow in rate, the default value is 1000.
7. `topic.per.stable`: If it's set to true, it means one super table in TDengine corresponds to a topic in Kafka, the topic naming rule is `<topic.prefix>-<connection.database>-<stable.name>`; if it's set to false, it means the whole DB corresponds to a topic in Kafka, the topic naming rule is `<topic.prefix>-<connection.database>`.
6. `query.interval.ms`: The time range of reading data from TDengine each time, its unit is millisecond. It should be adjusted according to the data flow in rate, the default value is 0, this means to get all the data to the latest time.
7. `out.format`: Result output format. `line` indicates that the output format is InfluxDB line protocol format, `json` indicates that the output format is json. The default is line.
8. `topic.per.stable`: If it's set to true, it means one super table in TDengine corresponds to a topic in Kafka, the topic naming rule is `<topic.prefix>-<connection.database>-<stable.name>`; if it's set to false, it means the whole DB corresponds to a topic in Kafka, the topic naming rule is `<topic.prefix>-<connection.database>`.
9. `topic.ignore.db`: Whether the topic naming rule contains the database name: true indicates that the rule is `<topic.prefix>-<stable.name>`, false indicates that the rule is `<topic.prefix>-<connection.database>-<stable.name>`, and the default is false. Does not take effect when `topic.per.stable` is set to false.
## Other notes
1. To install plugin to a customized location, refer to https://docs.confluent.io/home/connect/self-managed/install.html#install-connector-manually.
2. To use Kafka Connect without confluent, refer to https://kafka.apache.org/documentation/#connect.
1. To use Kafka Connect, refer to <https://kafka.apache.org/documentation/#connect>.
## Feedback
https://github.com/taosdata/kafka-connect-tdengine/issues
<https://github.com/taosdata/kafka-connect-tdengine/issues>
## Reference
1. https://www.confluent.io/what-is-apache-kafka
2. https://developer.confluent.io/learn-kafka/kafka-connect/intro
3. https://docs.confluent.io/platform/current/platform.html
1. For more information, see <https://kafka.apache.org/documentation/>
docs/en/28-releases/01-tdengine.md
浏览文件 @ 3689b41f
......@@ -10,6 +10,14 @@ For TDengine 2.x installation packages by version, please visit [here](https://w
import Release from "/components/ReleaseV3";
## 3.0.5.0
<Release type="tdengine" version="3.0.5.0" />
## 3.0.4.2
<Release type="tdengine" version="3.0.4.2" />
## 3.0.4.1
<Release type="tdengine" version="3.0.4.1" />
......
docs/en/28-releases/02-tools.md
浏览文件 @ 3689b41f
......@@ -10,6 +10,10 @@ For other historical version installers, please visit [here](https://www.taosdat
import Release from "/components/ReleaseV3";
## 2.5.1
<Release type="tools" version="2.5.1" />
## 2.5.0
<Release type="tools" version="2.5.0" />
......
docs/examples/c/async_query_example.c
浏览文件 @ 3689b41f
......@@ -78,7 +78,8 @@ int printRow(char *str, TAOS_ROW row, TAOS_FIELD *fields, int numFields) {
} break;
case TSDB_DATA_TYPE_BINARY:
case TSDB_DATA_TYPE_NCHAR: {
case TSDB_DATA_TYPE_NCHAR:
case TSDB_DATA_TYPE_GEOMETRY: {
int32_t charLen = varDataLen((char *)row[i] - VARSTR_HEADER_SIZE);
memcpy(str + len, row[i], charLen);
len += charLen;
......
docs/examples/c/query_example.c
浏览文件 @ 3689b41f
......@@ -76,7 +76,8 @@ int printRow(char *str, TAOS_ROW row, TAOS_FIELD *fields, int numFields) {
} break;
case TSDB_DATA_TYPE_BINARY:
case TSDB_DATA_TYPE_NCHAR: {
case TSDB_DATA_TYPE_NCHAR:
case TSDB_DATA_TYPE_GEOMETRY: {
int32_t charLen = varDataLen((char *)row[i] - VARSTR_HEADER_SIZE);
memcpy(str + len, row[i], charLen);
len += charLen;
......
docs/examples/java/src/main/java/com/taos/example/StmtInsertExample.java
浏览文件 @ 3689b41f
......@@ -6,39 +6,32 @@ import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;
import java.sql.Statement;
import java.text.SimpleDateFormat;
import java.time.LocalDateTime;
import java.time.ZoneOffset;
import java.time.format.DateTimeFormatter;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.List;
import java.util.Random;
import java.util.stream.Collectors;
public class StmtInsertExample {
private static ArrayList<Long> tsToLongArray(String ts) {
ArrayList<Long> result = new ArrayList<>();
DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss.SSS");
LocalDateTime localDateTime = LocalDateTime.parse(ts, formatter);
result.add(localDateTime.toInstant(ZoneOffset.of("+8")).toEpochMilli());
return result;
}
private static <T> ArrayList<T> toArray(T v) {
ArrayList<T> result = new ArrayList<>();
result.add(v);
return result;
}
private static String datePattern = "yyyy-MM-dd HH:mm:ss.SSS";
private static DateTimeFormatter formatter = DateTimeFormatter.ofPattern(datePattern);
private static List<String> getRawData() {
return Arrays.asList(
"d1001,2018-10-03 14:38:05.000,10.30000,219,0.31000,California.SanFrancisco,2",
"d1001,2018-10-03 14:38:15.000,12.60000,218,0.33000,California.SanFrancisco,2",
"d1001,2018-10-03 14:38:16.800,12.30000,221,0.31000,California.SanFrancisco,2",
"d1002,2018-10-03 14:38:16.650,10.30000,218,0.25000,California.SanFrancisco,3",
"d1003,2018-10-03 14:38:05.500,11.80000,221,0.28000,California.LosAngeles,2",
"d1003,2018-10-03 14:38:16.600,13.40000,223,0.29000,California.LosAngeles,2",
"d1004,2018-10-03 14:38:05.000,10.80000,223,0.29000,California.LosAngeles,3",
"d1004,2018-10-03 14:38:06.500,11.50000,221,0.35000,California.LosAngeles,3"
);
private static List<String> getRawData(int size) {
SimpleDateFormat format = new SimpleDateFormat(datePattern);
List<String> result = new ArrayList<>();
long current = System.currentTimeMillis();
Random random = new Random();
for (int i = 0; i < size; i++) {
String time = format.format(current + i);
int id = random.nextInt(10);
result.add("d" + id + "," + time + ",10.30000,219,0.31000,California.SanFrancisco,2");
}
return result.stream()
.sorted(Comparator.comparing(s -> s.split(",")[0])).collect(Collectors.toList());
}
private static Connection getConnection() throws SQLException {
......@@ -48,9 +41,9 @@ public class StmtInsertExample {
private static void createTable(Connection conn) throws SQLException {
try (Statement stmt = conn.createStatement()) {
stmt.execute("CREATE DATABASE power KEEP 3650");
stmt.executeUpdate("USE power");
stmt.execute("CREATE STABLE meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) " +
stmt.execute("CREATE DATABASE if not exists power KEEP 3650");
stmt.executeUpdate("use power");
stmt.execute("CREATE STABLE if not exists meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) " +
"TAGS (location BINARY(64), groupId INT)");
}
}
......@@ -58,21 +51,54 @@ public class StmtInsertExample {
private static void insertData() throws SQLException {
try (Connection conn = getConnection()) {
createTable(conn);
String psql = "INSERT INTO ? USING meters TAGS(?, ?) VALUES(?, ?, ?, ?)";
String psql = "INSERT INTO ? USING power.meters TAGS(?, ?) VALUES(?, ?, ?, ?)";
try (TSDBPreparedStatement pst = (TSDBPreparedStatement) conn.prepareStatement(psql)) {
for (String line : getRawData()) {
String tableName = null;
ArrayList<Long> ts = new ArrayList<>();
ArrayList<Float> current = new ArrayList<>();
ArrayList<Integer> voltage = new ArrayList<>();
ArrayList<Float> phase = new ArrayList<>();
for (String line : getRawData(100000)) {
String[] ps = line.split(",");
// bind table name and tags
pst.setTableName(ps[0]);
pst.setTagString(0, ps[5]);
pst.setTagInt(1, Integer.valueOf(ps[6]));
if (tableName == null) {
// bind table name and tags
tableName = "power." + ps[0];
pst.setTableName(ps[0]);
pst.setTagString(0, ps[5]);
pst.setTagInt(1, Integer.valueOf(ps[6]));
} else {
if (!tableName.equals(ps[0])) {
pst.setTimestamp(0, ts);
pst.setFloat(1, current);
pst.setInt(2, voltage);
pst.setFloat(3, phase);
pst.columnDataAddBatch();
pst.columnDataExecuteBatch();
// bind table name and tags
tableName = ps[0];
pst.setTableName(ps[0]);
pst.setTagString(0, ps[5]);
pst.setTagInt(1, Integer.valueOf(ps[6]));
ts.clear();
current.clear();
voltage.clear();
phase.clear();
}
}
// bind values
pst.setTimestamp(0, tsToLongArray(ps[1])); //ps[1] looks like: 2018-10-03 14:38:05.000
pst.setFloat(1, toArray(Float.valueOf(ps[2])));
pst.setInt(2, toArray(Integer.valueOf(ps[3])));
pst.setFloat(3, toArray(Float.valueOf(ps[4])));
pst.columnDataAddBatch();
// ps[1] looks like: 2018-10-03 14:38:05.000
LocalDateTime localDateTime = LocalDateTime.parse(ps[1], formatter);
ts.add(localDateTime.toInstant(ZoneOffset.of("+8")).toEpochMilli());
current.add(Float.valueOf(ps[2]));
voltage.add(Integer.valueOf(ps[3]));
phase.add(Float.valueOf(ps[4]));
}
pst.setTimestamp(0, ts);
pst.setFloat(1, current);
pst.setInt(2, voltage);
pst.setFloat(3, phase);
pst.columnDataAddBatch();
pst.columnDataExecuteBatch();
}
}
......
docs/examples/java/src/main/java/com/taos/example/SubscribeDemo.java
浏览文件 @ 3689b41f
......@@ -53,20 +53,28 @@ public class SubscribeDemo {
// create consumer
Properties properties = new Properties();
properties.getProperty(TMQConstants.CONNECT_TYPE, "jni");
properties.setProperty(TMQConstants.BOOTSTRAP_SERVERS, "127.0.0.1:6030");
properties.setProperty(TMQConstants.CONNECT_USER, "root");
properties.setProperty(TMQConstants.CONNECT_PASS, "taosdata");
properties.setProperty(TMQConstants.MSG_WITH_TABLE_NAME, "true");
properties.setProperty(TMQConstants.ENABLE_AUTO_COMMIT, "true");
properties.setProperty(TMQConstants.GROUP_ID, "test");
properties.setProperty(TMQConstants.AUTO_COMMIT_INTERVAL, "1000");
properties.setProperty(TMQConstants.GROUP_ID, "test1");
properties.setProperty(TMQConstants.CLIENT_ID, "1");
properties.setProperty(TMQConstants.AUTO_OFFSET_RESET, "earliest");
properties.setProperty(TMQConstants.VALUE_DESERIALIZER,
"com.taos.example.MetersDeserializer");
properties.setProperty(TMQConstants.VALUE_DESERIALIZER_ENCODING, "UTF-8");
properties.setProperty(TMQConstants.EXPERIMENTAL_SNAPSHOT_ENABLE, "true");
// poll data
try (TaosConsumer<Meters> consumer = new TaosConsumer<>(properties)) {
consumer.subscribe(Collections.singletonList(TOPIC));
while (!shutdown.get()) {
ConsumerRecords<Meters> meters = consumer.poll(Duration.ofMillis(100));
for (ConsumerRecord<Meters> recode : meters) {
Meters meter = recode.value();
for (ConsumerRecord<Meters> r : meters) {
Meters meter = r.value();
System.out.println(meter);
}
}
......
docs/examples/java/src/main/java/com/taos/example/WebsocketSubscribeDemo.java
浏览文件 @ 3689b41f
package com.taos.example;
import com.taosdata.jdbc.tmq.ConsumerRecord;
import com.taosdata.jdbc.tmq.ConsumerRecords;
import com.taosdata.jdbc.tmq.TMQConstants;
import com.taosdata.jdbc.tmq.TaosConsumer;
......@@ -54,18 +55,26 @@ public class WebsocketSubscribeDemo {
Properties properties = new Properties();
properties.setProperty(TMQConstants.BOOTSTRAP_SERVERS, "127.0.0.1:6041");
properties.setProperty(TMQConstants.CONNECT_TYPE, "ws");
properties.setProperty(TMQConstants.CONNECT_USER, "root");
properties.setProperty(TMQConstants.CONNECT_PASS, "taosdata");
properties.setProperty(TMQConstants.AUTO_OFFSET_RESET, "earliest");
properties.setProperty(TMQConstants.MSG_WITH_TABLE_NAME, "true");
properties.setProperty(TMQConstants.ENABLE_AUTO_COMMIT, "true");
properties.setProperty(TMQConstants.GROUP_ID, "test");
properties.setProperty(TMQConstants.AUTO_COMMIT_INTERVAL, "1000");
properties.setProperty(TMQConstants.GROUP_ID, "test2");
properties.setProperty(TMQConstants.CLIENT_ID, "1");
properties.setProperty(TMQConstants.VALUE_DESERIALIZER,
"com.taos.example.MetersDeserializer");
properties.setProperty(TMQConstants.VALUE_DESERIALIZER_ENCODING, "UTF-8");
properties.setProperty(TMQConstants.EXPERIMENTAL_SNAPSHOT_ENABLE, "true");
// poll data
try (TaosConsumer<Meters> consumer = new TaosConsumer<>(properties)) {
consumer.subscribe(Collections.singletonList(TOPIC));
while (!shutdown.get()) {
ConsumerRecords<Meters> meters = consumer.poll(Duration.ofMillis(100));
for (Meters meter : meters) {
for (ConsumerRecord<Meters> r : meters) {
Meters meter = (Meters) r.value();
System.out.println(meter);
}
}
......
docs/examples/python/tmq_assignment_example.py 0 → 100644
浏览文件 @ 3689b41f
import taos
from taos.tmq import Consumer
import taosws
def prepare():
conn = taos.connect()
conn.execute("drop topic if exists tmq_assignment_demo_topic")
conn.execute("drop database if exists tmq_assignment_demo_db")
conn.execute("create database if not exists tmq_assignment_demo_db wal_retention_period 3600")
conn.select_db("tmq_assignment_demo_db")
conn.execute(
"create table if not exists tmq_assignment_demo_table (ts timestamp, c1 int, c2 float, c3 binary(10)) tags(t1 int)")
conn.execute(
"create topic if not exists tmq_assignment_demo_topic as select ts, c1, c2, c3 from tmq_assignment_demo_table")
conn.execute("insert into d0 using tmq_assignment_demo_table tags (0) values (now-2s, 1, 1.0, 'tmq test')")
conn.execute("insert into d0 using tmq_assignment_demo_table tags (0) values (now-1s, 2, 2.0, 'tmq test')")
conn.execute("insert into d0 using tmq_assignment_demo_table tags (0) values (now, 3, 3.0, 'tmq test')")
def taos_get_assignment_and_seek_demo():
prepare()
consumer = Consumer(
{
"group.id": "0",
# should disable snapshot,
# otherwise it will cause invalid params error
"experimental.snapshot.enable": "false",
}
)
consumer.subscribe(["tmq_assignment_demo_topic"])
# get topic assignment
assignments = consumer.assignment()
for assignment in assignments:
print(assignment)
# poll
consumer.poll(1)
consumer.poll(1)
# get topic assignment again
after_pool_assignments = consumer.assignment()
for assignment in after_pool_assignments:
print(assignment)
# seek to the beginning
for assignment in assignments:
consumer.seek(assignment)
# now the assignment should be the same as before poll
assignments = consumer.assignment()
for assignment in assignments:
print(assignment)
if __name__ == '__main__':
taosws_get_assignment_and_seek_demo()
docs/examples/python/tmq_websocket_assgnment_example.py 0 → 100644
浏览文件 @ 3689b41f
import taos
import taosws
def prepare():
conn = taos.connect()
conn.execute("drop topic if exists tmq_assignment_demo_topic")
conn.execute("drop database if exists tmq_assignment_demo_db")
conn.execute("create database if not exists tmq_assignment_demo_db wal_retention_period 3600")
conn.select_db("tmq_assignment_demo_db")
conn.execute(
"create table if not exists tmq_assignment_demo_table (ts timestamp, c1 int, c2 float, c3 binary(10)) tags(t1 int)")
conn.execute(
"create topic if not exists tmq_assignment_demo_topic as select ts, c1, c2, c3 from tmq_assignment_demo_table")
conn.execute("insert into d0 using tmq_assignment_demo_table tags (0) values (now-2s, 1, 1.0, 'tmq test')")
conn.execute("insert into d0 using tmq_assignment_demo_table tags (0) values (now-1s, 2, 2.0, 'tmq test')")
conn.execute("insert into d0 using tmq_assignment_demo_table tags (0) values (now, 3, 3.0, 'tmq test')")
def taosws_get_assignment_and_seek_demo():
prepare()
consumer = taosws.Consumer(conf={
"td.connect.websocket.scheme": "ws",
# should disable snapshot,
# otherwise it will cause invalid params error
"experimental.snapshot.enable": "false",
"group.id": "0",
})
consumer.subscribe(["tmq_assignment_demo_topic"])
# get topic assignment
assignments = consumer.assignment()
for assignment in assignments:
print(assignment.to_string())
# poll
consumer.poll(1)
consumer.poll(1)
# get topic assignment again
after_poll_assignments = consumer.assignment()
for assignment in after_poll_assignments:
print(assignment.to_string())
# seek to the beginning
for assignment in assignments:
for a in assignment.assignments():
consumer.seek(assignment.topic(), a.vg_id(), a.offset())
# now the assignment should be the same as before poll
assignments = consumer.assignment()
for assignment in assignments:
print(assignment.to_string())
if __name__ == '__main__':
taosws_get_assignment_and_seek_demo()
docs/zh/07-develop/01-connect/index.md
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......@@ -82,7 +82,7 @@ TDengine 提供了丰富的应用程序开发接口，为了便于用户快速
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>3.0.0</version>
<version>3.2.1</version>
</dependency>
```
......
docs/zh/07-develop/07-tmq.mdx
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......@@ -105,6 +105,12 @@ class Consumer:
def poll(self, timeout: float = 1.0):
pass
def assignment(self):
pass
def seek(self, partition):
pass
def close(self):
pass
......
docs/zh/07-develop/09-udf.md
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此差异已折叠。
docs/zh/08-connector/14-java.mdx
浏览文件 @ 3689b41f
此差异已折叠。
docs/zh/08-connector/20-go.mdx
浏览文件 @ 3689b41f
......@@ -30,7 +30,7 @@ REST 连接支持所有能运行 Go 的平台。
## 版本支持
请参考[版本支持列表](../#版本支持)
请参考[版本支持列表](https://github.com/taosdata/driver-go#remind)
## 支持的功能特性
......@@ -383,6 +383,15 @@ func main() {
提交消息。
* `func (c *Consumer) Assignment() (partitions []tmq.TopicPartition, err error)`
获取消费进度。(需要 TDengine >= 3.0.5.0， driver-go >= v3.5.0)
* `func (c *Consumer) Seek(partition tmq.TopicPartition, ignoredTimeoutMs int) error`
注意：出于兼容目的保留 `ignoredTimeoutMs` 参数，当前未使用
按照指定的进度消费。(需要 TDengine >= 3.0.5.0， driver-go >= v3.5.0)
* `func (c *Consumer) Close() error`
关闭连接。
......@@ -468,11 +477,20 @@ func main() {
提交消息。
* `func (c *Consumer) Assignment() (partitions []tmq.TopicPartition, err error)`
获取消费进度。(需要 TDengine >= 3.0.5.0， driver-go >= v3.5.0)
* `func (c *Consumer) Seek(partition tmq.TopicPartition, ignoredTimeoutMs int) error`
注意：出于兼容目的保留 `ignoredTimeoutMs` 参数，当前未使用
按照指定的进度消费。(需要 TDengine >= 3.0.5.0， driver-go >= v3.5.0)
* `func (c *Consumer) Close() error`
关闭连接。
完整订阅示例参见 [GitHub 示例文件](https://github.com/taosdata/driver-go/blob/3.0/examples/tmqoverws/main.go)
完整订阅示例参见 [GitHub 示例文件](https://github.com/taosdata/driver-go/blob/main/examples/tmqoverws/main.go)
### 通过 WebSocket 进行参数绑定
......@@ -520,7 +538,7 @@ func main() {
结束参数绑定。
完整参数绑定示例参见 [GitHub 示例文件](https://github.com/taosdata/driver-go/blob/3.0/examples/stmtoverws/main.go)
完整参数绑定示例参见 [GitHub 示例文件](https://github.com/taosdata/driver-go/blob/main/examples/stmtoverws/main.go)
## API 参考
......
docs/zh/08-connector/26-rust.mdx
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......@@ -26,9 +26,14 @@ import RustQuery from "../07-develop/04-query-data/_rust.mdx"
原生连接支持的平台和 TDengine 客户端驱动支持的平台一致。
Websocket 连接支持所有能运行 Rust 的平台。
## 版本支持
## 版本历史
请参考[版本支持列表](../#版本支持)
| Rust 连接器版本 | TDengine 版本 | 主要功能 |
| :----------------: | :--------------: | :--------------------------------------------------: |
| v0.8.10 | 3.0.5.0 or later | 消息订阅：获取消费进度及按照指定进度开始消费。 |
| v0.8.0 | 3.0.4.0 | 支持无模式写入。 |
| v0.7.6 | 3.0.3.0 | 支持在请求中使用 req_id。 |
| v0.6.0 | 3.0.0.0 | 基础功能。 |
Rust 连接器仍然在快速开发中，1.0 之前无法保证其向后兼容。建议使用 3.0 版本以上的 TDengine，以避免已知问题。
......@@ -65,6 +70,13 @@ taos = "*"
taos = { version = "*", default-features = false, features = ["ws"] }
```
当仅启用 `ws` 特性时，可同时指定 `r2d2` 使得在同步（blocking/sync）模式下使用 [r2d2] 作为连接池：
```toml
[dependencies]
taos = { version = "*", default-features = false, features = ["r2d2", "ws"] }
```
</TabItem>
<TabItem value="native" label="仅原生连接">
......@@ -257,26 +269,24 @@ let conn: Taos = cfg.build();
### 连接池
在复杂应用中，建议启用连接池。[taos] 的连接池使用 [r2d2] 实现。
在复杂应用中，建议启用连接池。[taos] 的连接池默认（异步模式）使用 [deadpool] 实现。
如下，可以生成一个默认参数的连接池。
```rust
let pool = TaosBuilder::from_dsn(dsn)?.pool()?;
let pool: Pool<TaosBuilder> = TaosBuilder::from_dsn("taos:///")
.unwrap()
.pool()
.unwrap();
```
同样可以使用连接池的构造器，对连接池参数进行设置：
```rust
let dsn = "taos://localhost:6030";
let opts = PoolBuilder::new()
.max_size(5000) // max connections
.max_lifetime(Some(Duration::from_secs(60 * 60))) // lifetime of each connection
.min_idle(Some(1000)) // minimal idle connections
.connection_timeout(Duration::from_secs(2));
let pool = TaosBuilder::from_dsn(dsn)?.with_pool_builder(opts)?;
let pool: Pool<TaosBuilder> = Pool::builder(Manager::from_dsn(self.dsn.clone()).unwrap().0)
.max_size(88) // 最大连接数
.build()
.unwrap();
```
在应用代码中，使用 `pool.get()?` 来获取一个连接对象 [Taos]。
......@@ -497,6 +507,22 @@ TMQ 消息队列是一个 [futures::Stream](https://docs.rs/futures/latest/futur
}
```
获取消费进度：
版本要求 connector-rust >= v0.8.8， TDengine >= 3.0.5.0
```rust
let assignments = consumer.assignments().await.unwrap();
```
按照指定的进度消费：
版本要求 connector-rust >= v0.8.8， TDengine >= 3.0.5.0
```rust
consumer.offset_seek(topic, vgroup_id, offset).await;
```
停止订阅：
```rust
......@@ -511,11 +537,12 @@ consumer.unsubscribe().await;
- `enable.auto.commit`: 当设置为 `true` 时，将启用自动标记模式，当对数据一致性不敏感时，可以启用此方式。
- `auto.commit.interval.ms`: 自动标记的时间间隔。
完整订阅示例参见 [GitHub 示例文件](https://github.com/taosdata/taos-connector-rust/blob/main/examples/subscribe.rs).
完整订阅示例参见 [GitHub 示例文件](https://github.com/taosdata/TDengine/blob/3.0/docs/examples/rust/nativeexample/examples/subscribe_demo.rs).
其他相关结构体 API 使用说明请移步 Rust 文档托管网页：<https://docs.rs/taos>。
[taos]: https://github.com/taosdata/rust-connector-taos
[deadpool]: https://crates.io/crates/deadpool
[r2d2]: https://crates.io/crates/r2d2
[TaosBuilder]: https://docs.rs/taos/latest/taos/struct.TaosBuilder.html
[TaosCfg]: https://docs.rs/taos/latest/taos/struct.TaosCfg.html
......
docs/zh/08-connector/30-python.mdx
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......@@ -362,7 +362,7 @@ TaosCursor 类使用原生连接进行写入、查询操作。在客户端多线
##### TaosConnection 类的使用
`TaosConnection` 类既包含对 PEP249 Connection 接口的实现(如：`cursor`方法和 `close` 方法)，也包含很多扩展功能（如： `execute`、 `query`、`schemaless_insert` 和 `subscribe` 方法。
类似上文介绍的使用方法，增加 `req_id` 参数。
```python title="execute 方法"
{{#include docs/examples/python/connection_usage_native_reference_with_req_id.py:insert}}
......@@ -372,13 +372,9 @@ TaosCursor 类使用原生连接进行写入、查询操作。在客户端多线
{{#include docs/examples/python/connection_usage_native_reference_with_req_id.py:query}}
```
:::tip
查询结果只能获取一次。比如上面的示例中 `fetch_all()` 和 `fetch_all_into_dict()` 只能用一个。重复获取得到的结果为空列表。
:::
##### TaosResult 类的使用
上面 `TaosConnection` 类的使用示例中，我们已经展示了两种获取查询结果的方法： `fetch_all()` 和 `fetch_all_into_dict()`。除此之外 `TaosResult` 还提供了按行迭代(`rows_iter`)或按数据块迭代(`blocks_iter`)结果集的方法。在查询数据量较大的场景，使用这两个方法会更高效。
类似上文介绍的使用方法，增加 `req_id` 参数。
```python title="blocks_iter 方法"
{{#include docs/examples/python/result_set_with_req_id_examples.py}}
......@@ -391,14 +387,11 @@ TaosCursor 类使用原生连接进行写入、查询操作。在客户端多线
{{#include docs/examples/python/cursor_usage_native_reference_with_req_id.py}}
```
:::note
TaosCursor 类使用原生连接进行写入、查询操作。在客户端多线程的场景下，这个游标实例必须保持线程独享，不能跨线程共享使用，否则会导致返回结果出现错误。
:::
</TabItem>
<TabItem value="rest" label="REST 连接">
类似上文介绍的使用方法，增加 `req_id` 参数。
##### TaosRestCursor 类的使用
`TaosRestCursor` 类是对 PEP249 Cursor 接口的实现。
......@@ -420,8 +413,11 @@ TaosCursor 类使用原生连接进行写入、查询操作。在客户端多线
对于 `sql()` 方法更详细的介绍， 请参考 [RestClient](https://docs.taosdata.com/api/taospy/taosrest/restclient.html)。
</TabItem>
<TabItem value="websocket" label="WebSocket 连接">
类似上文介绍的使用方法，增加 `req_id` 参数。
```python
{{#include docs/examples/python/connect_websocket_with_req_id_examples.py:basic}}
```
......@@ -460,27 +456,169 @@ TaosCursor 类使用原生连接进行写入、查询操作。在客户端多线
### 数据订阅
连接器支持数据订阅功能，数据订阅功能请参考 [数据订阅](../../develop/tmq/)。
连接器支持数据订阅功能，数据订阅功能请参考 [数据订阅文档](../../develop/tmq/)。
<Tabs defaultValue="native">
<TabItem value="native" label="原生连接">
`Consumer` 提供了 Python 连接器订阅 TMQ 数据的 API，相关 API 定义请参考 [数据订阅文档](../../develop/tmq/#%E4%B8%BB%E8%A6%81%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E5%92%8C-api)。
`Consumer` 提供了 Python 连接器订阅 TMQ 数据的 API。
#### 创建 Consumer
创建 Consumer 语法为 `consumer = Consumer(configs)`，参数定义请参考 [数据订阅文档](../../develop/tmq/#%E5%88%9B%E5%BB%BA%E6%B6%88%E8%B4%B9%E8%80%85-consumer)。
```python
from taos.tmq import Consumer
consumer = Consumer({"group.id": "local", "td.connect.ip": "127.0.0.1"})
```
#### 订阅 topics
Comsumer API 的 `subscribe` 方法用于订阅 topics，consumer 支持同时订阅多个 topic。
```python
consumer.subscribe(['topic1', 'topic2'])
```
#### 消费数据
Consumer API 的 `poll` 方法用于消费数据，`poll` 方法接收一个 float 类型的超时时间，超时时间单位为秒（s），`poll` 方法在超时之前返回一条 Message 类型的数据或超时返回 `None`。消费者必须通过 Message 的 `error()` 方法校验返回数据的 error 信息。
```python
while True:
res = consumer.poll(1)
if not res:
continue
err = res.error()
if err is not None:
raise err
val = res.value()
for block in val:
print(block.fetchall())
```
#### 获取消费进度
Consumer API 的 `assignment` 方法用于获取 Consumer 订阅的所有 topic 的消费进度，返回结果类型为 TopicPartition 列表。
```python
assignments = consumer.assignment()
```
#### 重置消费进度
Consumer API 的 `seek` 方法用于重置 Consumer 的消费进度到指定位置，方法参数类型为 TopicPartition。
```python
tp = TopicPartition(topic='topic1', partition=0, offset=0)
consumer.seek(tp)
```
#### 结束消费
消费结束后，应当取消订阅，并关闭 Consumer。
```python
consumer.unsubscribe()
consumer.close()
```
#### tmq 订阅示例代码
```python
{{#include docs/examples/python/tmq_example.py}}
```
#### 获取和重置消费进度示例代码
```python
{{#include docs/examples/python/tmq_assignment_example.py:taos_get_assignment_and_seek_demo}}
```
</TabItem>
<TabItem value="websocket" label="WebSocket 连接">
除了原生的连接方式，Python 连接器还支持通过 websocket 订阅 TMQ 数据。
除了原生的连接方式，Python 连接器还支持通过 websocket 订阅 TMQ 数据，使用 websocket 方式订阅 TMQ 数据需要安装 `taos-ws-py`。
taosws `Consumer` API 提供了基于 Websocket 订阅 TMQ 数据的 API。
#### 创建 Consumer
创建 Consumer 语法为 `consumer = Consumer(conf=configs)`，使用时需要指定 `td.connect.websocket.scheme` 参数值为 "ws"，参数定义请参考 [数据订阅文档](../../develop/tmq/#%E5%88%9B%E5%BB%BA%E6%B6%88%E8%B4%B9%E8%80%85-consumer)。
```python
import taosws
consumer = taosws.(conf={"group.id": "local", "td.connect.websocket.scheme": "ws"})
```
#### 订阅 topics
Comsumer API 的 `subscribe` 方法用于订阅 topics，consumer 支持同时订阅多个 topic。
```python
consumer.subscribe(['topic1', 'topic2'])
```
#### 消费数据
Consumer API 的 `poll` 方法用于消费数据，`poll` 方法接收一个 float 类型的超时时间，超时时间单位为秒（s），`poll` 方法在超时之前返回一条 Message 类型的数据或超时返回 `None`。消费者必须通过 Message 的 `error()` 方法校验返回数据的 error 信息。
```python
while True:
res = consumer.poll(timeout=1.0)
if not res:
continue
err = res.error()
if err is not None:
raise err
for block in message:
for row in block:
print(row)
```
#### 获取消费进度
Consumer API 的 `assignment` 方法用于获取 Consumer 订阅的所有 topic 的消费进度，返回结果类型为 TopicPartition 列表。
```python
assignments = consumer.assignment()
```
#### 重置消费进度
Consumer API 的 `seek` 方法用于重置 Consumer 的消费进度到指定位置。
```python
consumer.seek(topic='topic1', partition=0, offset=0)
```
#### 结束消费
消费结束后，应当取消订阅，并关闭 Consumer。
```python
consumer.unsubscribe()
consumer.close()
```
#### tmq 订阅示例代码
```python
{{#include docs/examples/python/tmq_websocket_example.py}}
```
连接器提供了 `assignment` 接口，用于获取 topic assignment 的功能，可以查询订阅的 topic 的消费进度，并提供 `seek` 接口，用于重置 topic 的消费进度。
#### 获取和重置消费进度示例代码
```python
{{#include docs/examples/python/tmq_websocket_assgnment_example.py:taosws_get_assignment_and_seek_demo}}
```
</TabItem>
</Tabs>
......
docs/zh/08-connector/index.md
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......@@ -45,7 +45,7 @@ TDengine 版本更新往往会增加新的功能特性，列表中的连接器
| **连接管理** | 支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **普通查询** | 支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **参数绑定** | 支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **数据订阅（TMQ）** | 支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **数据订阅（TMQ）** | 暂不支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **Schemaless** | 支持 | 支持 | 支持 | 支持 | 支持 | 支持 |
| **DataFrame** | 不支持 | 支持 | 不支持 | 不支持 | 不支持 | 不支持 |
......
docs/zh/12-taos-sql/01-data-type.md
浏览文件 @ 3689b41f
......@@ -45,9 +45,9 @@ CREATE DATABASE db_name PRECISION 'ns';
:::note
- 表的每行长度不能超过 48KB（注意：每个 BINARY/NCHAR 类型的列还会额外占用 2 个字节的存储位置）。
- 表的每行长度不能超过 48KB（从 3.0.5.0 版本开始为 64KB）（注意：每个 BINARY/NCHAR 类型的列还会额外占用 2 个字节的存储位置）。
- 虽然 BINARY 类型在底层存储上支持字节型的二进制字符，但不同编程语言对二进制数据的处理方式并不保证一致，因此建议在 BINARY 类型中只存储 ASCII 可见字符，而避免存储不可见字符。多字节的数据，例如中文字符，则需要使用 NCHAR 类型进行保存。如果强行使用 BINARY 类型保存中文字符，虽然有时也能正常读写，但并不带有字符集信息，很容易出现数据乱码甚至数据损坏等情况。
- BINARY 类型理论上最长可以有 16,374 字节。BINARY 仅支持字符串输入，字符串两端需使用单引号引用。使用时须指定大小，如 BINARY(20) 定义了最长为 20 个单字节字符的字符串，每个字符占 1 字节的存储空间，总共固定占用 20 字节的空间，此时如果用户字符串超出 20 字节将会报错。对于字符串内的单引号，可以用转义字符反斜线加单引号来表示，即 `\'`。
- BINARY 类型理论上最长可以有 16,374（从 3.0.5.0 版本开始，数据列为 65,517，标签列为 16,382） 字节。BINARY 仅支持字符串输入，字符串两端需使用单引号引用。使用时须指定大小，如 BINARY(20) 定义了最长为 20 个单字节字符的字符串，每个字符占 1 字节的存储空间，总共固定占用 20 字节的空间，此时如果用户字符串超出 20 字节将会报错。对于字符串内的单引号，可以用转义字符反斜线加单引号来表示，即 `\'`。
- SQL 语句中的数值类型将依据是否存在小数点，或使用科学计数法表示，来判断数值类型是否为整型或者浮点型，因此在使用时要注意相应类型越界的情况。例如，9999999999999999999 会认为超过长整型的上边界而溢出，而 9999999999999999999.0 会被认为是有效的浮点数。
:::
......
docs/zh/12-taos-sql/02-database.md
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......@@ -121,6 +121,8 @@ alter_database_option: {
| WAL_LEVEL value
| WAL_FSYNC_PERIOD value
| KEEP value
| WAL_RETENTION_PERIOD value
| WAL_RETENTION_SIZE value
}
```
......
docs/zh/12-taos-sql/03-table.md
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......@@ -43,7 +43,7 @@ table_option: {
1. 表的第一个字段必须是 TIMESTAMP，并且系统自动将其设为主键；
2. 表名最大长度为 192；
3. 表的每行长度不能超过 48KB;（注意：每个 BINARY/NCHAR 类型的列还会额外占用 2 个字节的存储位置）
3. 表的每行长度不能超过 48KB（从 3.0.5.0 版本开始为 64KB）;（注意：每个 BINARY/NCHAR 类型的列还会额外占用 2 个字节的存储位置）
4. 子表名只能由字母、数字和下划线组成，且不能以数字开头，不区分大小写
5. 使用数据类型 binary 或 nchar，需指定其最长的字节数，如 binary(20)，表示 20 字节；
6. 为了兼容支持更多形式的表名，TDengine 引入新的转义符 "\`"，可以让表名与关键词不冲突，同时不受限于上述表名称合法性约束检查。但是同样具有长度限制要求。使用转义字符以后，不再对转义字符中的内容进行大小写统一。
......
docs/zh/12-taos-sql/06-select.md
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......@@ -55,7 +55,7 @@ window_clause: {
| INTERVAL(interval_val [, interval_offset]) [SLIDING (sliding_val)] [WATERMARK(watermark_val)] [FILL(fill_mod_and_val)]
interp_clause:
RANGE(ts_val, ts_val) EVERY(every_val) FILL(fill_mod_and_val)
RANGE(ts_val [, ts_val]) EVERY(every_val) FILL(fill_mod_and_val)
partition_by_clause:
PARTITION BY expr [, expr] ...
......
docs/zh/12-taos-sql/10-function.md
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......@@ -890,9 +890,10 @@ ignore_null_values: {
- INTERP 用于在指定时间断面获取指定列的记录值，如果该时间断面不存在符合条件的行数据，那么会根据 FILL 参数的设定进行插值。
- INTERP 的输入数据为指定列的数据，可以通过条件语句（where 子句）来对原始列数据进行过滤，如果没有指定过滤条件则输入为全部数据。
- INTERP 需要同时与 RANGE，EVERY 和 FILL 关键字一起使用。
- INTERP 的输出时间范围根据 RANGE(timestamp1,timestamp2)字段来指定，需满足 timestamp1 <= timestamp2。其中 timestamp1（必选值）为输出时间范围的起始值，即如果 timestamp1 时刻符合插值条件则 timestamp1 为输出的第一条记录，timestamp2（必选值）为输出时间范围的结束值，即输出的最后一条记录的 timestamp 不能大于 timestamp2。
- INTERP 的输出时间范围根据 RANGE(timestamp1, timestamp2)字段来指定，需满足 timestamp1 <= timestamp2。其中 timestamp1 为输出时间范围的起始值，即如果 timestamp1 时刻符合插值条件则 timestamp1 为输出的第一条记录，timestamp2 为输出时间范围的结束值，即输出的最后一条记录的 timestamp 不能大于 timestamp2。
- INTERP 根据 EVERY(time_unit) 字段来确定输出时间范围内的结果条数，即从 timestamp1 开始每隔固定长度的时间（time_unit 值）进行插值，time_unit 可取值时间单位：1a(毫秒)，1s(秒)，1m(分)，1h(小时)，1d(天)，1w(周)。例如 EVERY(500a) 将对于指定数据每500毫秒间隔进行一次插值.
- INTERP 根据 FILL 字段来决定在每个符合输出条件的时刻如何进行插值。关于 FILL 子句如何使用请参考 [FILL 子句](../distinguished/#fill-子句)
- INTERP 可以在 RANGE 字段中只指定唯一的时间戳对单个时间点进行插值，在这种情况下，EVERY 字段可以省略。例如：SELECT INTERP(col) FROM tb RANGE('2023-01-01 00:00:00') FILL(linear).
- INTERP 作用于超级表时, 会将该超级表下的所有子表数据按照主键列排序后进行插值计算，也可以搭配 PARTITION BY tbname 使用，将结果强制规约到单个时间线。
- INTERP 可以与伪列 _irowts 一起使用，返回插值点所对应的时间戳(3.0.2.0版本以后支持)。
- INTERP 可以与伪列 _isfilled 一起使用，显示返回结果是否为原始记录或插值算法产生的数据(3.0.3.0版本以后支持)。
......@@ -1001,7 +1002,6 @@ SAMPLE(expr, k)
**使用说明**：
- 不能参与表达式计算；该函数可以应用在普通表和超级表上；
- 使用在超级表上的时候，需要搭配 PARTITION by tbname 使用，将结果强制规约到单个时间线。
### TAIL
......@@ -1080,7 +1080,6 @@ CSUM(expr)
- 不支持 +、-、*、/ 运算，如 csum(col1) + csum(col2)。
- 只能与聚合（Aggregation）函数一起使用。 该函数可以应用在普通表和超级表上。
- 使用在超级表上的时候，需要搭配 PARTITION BY tbname使用，将结果强制规约到单个时间线。
### DERIVATIVE
......@@ -1104,7 +1103,6 @@ ignore_negative: {
**使用说明**:
- DERIVATIVE 函数可以在由 PARTITION BY 划分出单独时间线的情况下用于超级表（也即 PARTITION BY tbname）。
- 可以与选择相关联的列一起使用。 例如: select \_rowts, DERIVATIVE() from。
### DIFF
......@@ -1167,7 +1165,6 @@ MAVG(expr, k)
- 不支持 +、-、*、/ 运算，如 mavg(col1, k1) + mavg(col2, k1);
- 只能与普通列，选择（Selection）、投影（Projection）函数一起使用，不能与聚合（Aggregation）函数一起使用；
- 使用在超级表上的时候，需要搭配 PARTITION BY tbname使用，将结果强制规约到单个时间线。
### STATECOUNT
......@@ -1193,7 +1190,6 @@ STATECOUNT(expr, oper, val)
**使用说明**：
- 该函数可以应用在普通表上，在由 PARTITION BY 划分出单独时间线的情况下用于超级表（也即 PARTITION BY tbname）
- 不能和窗口操作一起使用，例如 interval/state_window/session_window。
......@@ -1221,7 +1217,6 @@ STATEDURATION(expr, oper, val, unit)
**使用说明**：
- 该函数可以应用在普通表上，在由 PARTITION BY 划分出单独时间线的情况下用于超级表（也即 PARTITION BY tbname）
- 不能和窗口操作一起使用，例如 interval/state_window/session_window。
......@@ -1239,8 +1234,6 @@ TWA(expr)
**适用于**：表和超级表。
**使用说明**： TWA 函数可以在由 PARTITION BY 划分出单独时间线的情况下用于超级表（也即 PARTITION BY tbname）。
## 系统信息函数
......
docs/zh/12-taos-sql/19-limit.md
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......@@ -26,7 +26,7 @@ description: 合法字符集和命名中的限制规则
- 数据库名最大长度为 64 字节
- 表名最大长度为 192 字节，不包括数据库名前缀和分隔符
- 每行数据最大长度 48KB （注意：数据行内每个 BINARY/NCHAR 类型的列还会额外占用 2 个字节的存储位置）
- 每行数据最大长度 48KB（从 3.0.5.0 版本开始为 64KB） （注意：数据行内每个 BINARY/NCHAR 类型的列还会额外占用 2 个字节的存储位置）
- 列名最大长度为 64 字节
- 最多允许 4096 列，最少需要 2 列，第一列必须是时间戳。
- 标签名最大长度为 64 字节
......
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......@@ -91,11 +91,30 @@ taos --dump-config
### maxShellConns
| 属性 | 说明 |
| -------- | ----------------------- |
| --------| ----------------------- |
| 适用范围 | 仅服务端适用 |
| 含义 | 一个 dnode 容许的连接数 |
| 含义 | 一个 dnode 容许的连接数 |
| 取值范围 | 10-50000000 |
| 缺省值 | 5000 |
| 缺省值 | 5000 |
### numOfRpcSessions
| 属性 | 说明 |
| --------| ---------------------- |
| 适用范围 | 客户端和服务端都适用 |
| 含义 | 一个客户端能创建的最大连接数|
| 取值范围 | 100-100000 |
| 缺省值 | 10000 |
### timeToGetAvailableConn
| 属性 | 说明 |
| -------- | --------------------|
| 适用范围 | 客户端和服务端都适用 |
| 含义 |获得可用连接的最长等待时间|
| 取值范围 | 10-50000000(单位为毫秒)|
| 缺省值 | 500000 |
### numOfRpcSessions
......
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......@@ -87,7 +87,7 @@ st,t1=3,t2=4,t3=t3 c1=3i64,c3="passit",c2=false,c4=4f64 1626006833639000000
:::tip
无模式所有的处理逻辑，仍会遵循 TDengine 对数据结构的底层限制，例如每行数据的总长度不能超过
48KB，标签值的总长度不超过16KB。这方面的具体限制约束请参见 [TDengine SQL 边界限制](/taos-sql/limit)
48KB（从 3.0.5.0 版本开始为 64KB），标签值的总长度不超过16KB。这方面的具体限制约束请参见 [TDengine SQL 边界限制](/taos-sql/limit)
:::
......
docs/zh/20-third-party/11-kafka.md
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......@@ -16,169 +16,78 @@ TDengine Source Connector 用于把数据实时地从 TDengine 读出来发送
![TDengine Database Kafka Connector -- streaming integration with kafka connect](kafka/streaming-integration-with-kafka-connect.webp)
## 什么是 Confluent？
[Confluent](https://www.confluent.io/) 在 Kafka 的基础上增加很多扩展功能。包括：
1. Schema Registry
2. REST 代理
3. 非 Java 客户端
4. 很多打包好的 Kafka Connect 插件
5. 管理和监控 Kafka 的 GUI —— Confluent 控制中心
这些扩展功能有的包含在社区版本的 Confluent 中，有的只有企业版能用。
![TDengine Database Kafka Connector -- Confluent introduction](kafka/confluentPlatform.webp)
Confluent 企业版提供了 `confluent` 命令行工具管理各个组件。
## 前置条件
运行本教程中示例的前提条件。
1. Linux 操作系统
2. 已安装 Java 8 和 Maven
3. 已安装 Git
3. 已安装 Git、curl、vi
4. 已安装并启动 TDengine。如果还没有可参考[安装和卸载](/operation/pkg-install)
## 安装 Confluent
Confluent 提供了 Docker 和二进制包两种安装方式。本文仅介绍二进制包方式安装。
## 安装 Kafka
在任意目录下执行：
```
curl -O http://packages.confluent.io/archive/7.1/confluent-7.1.1.tar.gz
tar xzf confluent-7.1.1.tar.gz -C /opt/
```shell
curl -O https://downloads.apache.org/kafka/3.4.0/kafka_2.13-3.4.0.tgz
tar xzf kafka_2.13-3.4.0.tgz -C /opt/
ln -s /opt/kafka_2.13-3.4.0 /opt/kafka
```
然后需要把 `$CONFLUENT_HOME/bin` 目录加入 PATH。
然后需要把 `$KAFKA_HOME/bin` 目录加入 PATH。
```title=".profile"
export CONFLUENT_HOME=/opt/confluent-7.1.1
export PATH=$CONFLUENT_HOME/bin:$PATH
export KAFKA_HOME=/opt/kafka
export PATH=$PATH:$KAFKA_HOME/bin
```
以上脚本可以追加到当前用户的 profile 文件（~/.profile 或 ~/.bash_profile）
安装完成之后，可以输入`confluent version`做简单验证：
```
# confluent version
confluent - Confluent CLI
Version: v2.6.1
Git Ref: 6d920590
Build Date: 2022-02-18T06:14:21Z
Go Version: go1.17.6 (linux/amd64)
Development: false
```
## 安装 TDengine Connector 插件
### 从源码安装
### 编译插件
```
```shell
git clone --branch 3.0 https://github.com/taosdata/kafka-connect-tdengine.git
cd kafka-connect-tdengine
mvn clean package
unzip -d $CONFLUENT_HOME/share/java/ target/components/packages/taosdata-kafka-connect-tdengine-*.zip
mvn clean package -Dmaven.test.skip=true
unzip -d $KAFKA_HOME/components/ target/components/packages/taosdata-kafka-connect-tdengine-*.zip
```
以上脚本先 clone 项目源码，然后用 Maven 编译打包。打包完成后在 `target/components/packages/` 目录生成了插件的 zip 包。把这个 zip 包解压到安装插件的路径即可。上面的示例中使用了内置的插件安装路径： `$CONFLUENT_HOME/share/java/`。
以上脚本先 clone 项目源码，然后用 Maven 编译打包。打包完成后在 `target/components/packages/` 目录生成了插件的 zip 包。把这个 zip 包解压到安装插件的路径即可。上面的示例中使用了内置的插件安装路径： `$KAFKA_HOME/components/`。
### 用 confluent-hub 安装
### 配置插件
[Confluent Hub](https://www.confluent.io/hub) 提供下载 Kafka Connect 插件的服务。在 TDengine Kafka Connector 发布到 Confluent Hub 后可以使用命令工具 `confluent-hub` 安装。
**TDengine Kafka Connector 目前没有正式发布，不能用这种方式安装**。
将 kafka-connect-tdengine 插件加入 `$KAFKA_HOME/config/connect-distributed.properties` 配置文件 plugin.path 中
## 启动 Confluent
```
confluent local services start
```properties
plugin.path=/usr/share/java,/opt/kafka/components
```
:::note
一定要先安装插件再启动 Confluent, 否则加载插件会失败。
:::
## 启动 Kafka
:::tip
若某组件启动失败，可尝试清空数据，重新启动。数据目录在启动时将被打印到控制台，比如 ：
```title="控制台输出日志" {1}
Using CONFLUENT_CURRENT: /tmp/confluent.106668
Starting ZooKeeper
ZooKeeper is [UP]
Starting Kafka
Kafka is [UP]
Starting Schema Registry
Schema Registry is [UP]
Starting Kafka REST
Kafka REST is [UP]
Starting Connect
Connect is [UP]
Starting ksqlDB Server
ksqlDB Server is [UP]
Starting Control Center
Control Center is [UP]
```
```shell
zookeeper-server-start.sh -daemon $KAFKA_HOME/config/zookeeper.properties
清空数据可执行 `rm -rf /tmp/confluent.106668`。
:::
kafka-server-start.sh -daemon $KAFKA_HOME/config/server.properties
### 验证各个组件是否启动成功
输入命令：
```
confluent local services status
```
如果各组件都启动成功，会得到如下输出：
```
Connect is [UP]
Control Center is [UP]
Kafka is [UP]
Kafka REST is [UP]
ksqlDB Server is [UP]
Schema Registry is [UP]
ZooKeeper is [UP]
connect-distributed.sh -daemon $KAFKA_HOME/config/connect-distributed.properties
```
### 验证插件是否安装成功
### 验证 kafka Connect 是否启动成功
在 Kafka Connect 组件完全启动后，可用以下命令列出成功加载的插件：
输入命令：
```
confluent local services connect plugin list
```shell
curl http://localhost:8083/connectors
```
如果成功安装，会输出如下：
```txt {4,9}
Available Connect Plugins:
[
{
"class": "com.taosdata.kafka.connect.sink.TDengineSinkConnector",
"type": "sink",
"version": "1.0.0"
},
{
"class": "com.taosdata.kafka.connect.source.TDengineSourceConnector",
"type": "source",
"version": "1.0.0"
},
......
```
如果各组件都启动成功，会得到如下输出：
如果插件安装失败，请检查 Kafka Connect 的启动日志是否有异常信息，用以下命令输出日志路径：
```txt
[]
```
echo `cat /tmp/confluent.current`/connect/connect.stdout
```
该命令的输出类似： `/tmp/confluent.104086/connect/connect.stdout`。
与日志文件 `connect.stdout` 同一目录，还有一个文件名为： `connect.properties`。在这个文件的末尾，可以看到最终生效的 `plugin.path`， 它是一系列用逗号分割的路径。如果插件安装失败，很可能是因为实际的安装路径不包含在 `plugin.path` 中。
## TDengine Sink Connector 的使用
......@@ -188,40 +97,47 @@ TDengine Sink Connector 内部使用 TDengine [无模式写入接口](../../conn
下面的示例将主题 meters 的数据，同步到目标数据库 power。数据格式为 InfluxDB Line 协议格式。
### 添加配置文件
### 添加 Sink Connector 配置文件
```
```shell
mkdir ~/test
cd ~/test
vi sink-demo.properties
vi sink-demo.json
```
sink-demo.properties 内容如下：
```ini title="sink-demo.properties"
name=TDengineSinkConnector
connector.class=com.taosdata.kafka.connect.sink.TDengineSinkConnector
tasks.max=1
topics=meters
connection.url=jdbc:TAOS://127.0.0.1:6030
connection.user=root
connection.password=taosdata
connection.database=power
db.schemaless=line
data.precision=ns
key.converter=org.apache.kafka.connect.storage.StringConverter
value.converter=org.apache.kafka.connect.storage.StringConverter
sink-demo.json 内容如下：
```json title="sink-demo.json"
{
"name": "TDengineSinkConnector",
"config": {
"connector.class":"com.taosdata.kafka.connect.sink.TDengineSinkConnector",
"tasks.max": "1",
"topics": "meters",
"connection.url": "jdbc:TAOS://127.0.0.1:6030",
"connection.user": "root",
"connection.password": "taosdata",
"connection.database": "power",
"db.schemaless": "line",
"data.precision": "ns",
"key.converter": "org.apache.kafka.connect.storage.StringConverter",
"value.converter": "org.apache.kafka.connect.storage.StringConverter",
"errors.tolerance": "all",
"errors.deadletterqueue.topic.name": "dead_letter_topic",
"errors.deadletterqueue.topic.replication.factor": 1
}
}
```
关键配置说明：
1. `topics=meters` 和 `connection.database=power`, 表示订阅主题 meters 的数据，并写入数据库 power。
2. `db.schemaless=line`, 表示使用 InfluxDB Line 协议格式的数据。
1. `"topics": "meters"` 和 `"connection.database": "power"`, 表示订阅主题 meters 的数据，并写入数据库 power。
2. `"db.schemaless": "line"`, 表示使用 InfluxDB Line 协议格式的数据。
### 创建 Connector 实例
### 创建 Sink Connector 实例
```
confluent local services connect connector load TDengineSinkConnector --config ./sink-demo.properties
```shell
curl -X POST -d @sink-demo.json http://localhost:8083/connectors -H "Content-Type: application/json"
```
若以上命令执行成功，则有如下输出：
......@@ -241,7 +157,10 @@ confluent local services connect connector load TDengineSinkConnector --config .
"tasks.max": "1",
"topics": "meters",
"value.converter": "org.apache.kafka.connect.storage.StringConverter",
"name": "TDengineSinkConnector"
"name": "TDengineSinkConnector",
"errors.tolerance": "all",
"errors.deadletterqueue.topic.name": "dead_letter_topic",
"errors.deadletterqueue.topic.replication.factor": "1",
},
"tasks": [],
"type": "sink"
......@@ -261,8 +180,8 @@ meters,location=California.LosAngeles,groupid=3 current=11.3,voltage=221,phase=0
使用 kafka-console-producer 向主题 meters 添加测试数据。
```
cat test-data.txt | kafka-console-producer --broker-list localhost:9092 --topic meters
```shell
cat test-data.txt | kafka-console-producer.sh --broker-list localhost:9092 --topic meters
```
:::note
......@@ -273,12 +192,12 @@ cat test-data.txt | kafka-console-producer --broker-list localhost:9092 --topic
使用 TDengine CLI 验证同步是否成功。
```
```sql
taos> use power;
Database changed.
taos> select * from meters;
ts | current | voltage | phase | groupid | location |
_ts | current | voltage | phase | groupid | location |
===============================================================================================================================================================
2022-03-28 09:56:51.249000000 | 11.800000000 | 221.000000000 | 0.280000000 | 2 | California.LosAngeles |
2022-03-28 09:56:51.250000000 | 13.400000000 | 223.000000000 | 0.290000000 | 2 | California.LosAngeles |
......@@ -297,29 +216,36 @@ TDengine Source Connector 会将 TDengine 数据表中的数据转换成 [Influx
下面的示例程序同步数据库 test 中的数据到主题 tdengine-source-test。
### 添加配置文件
### 添加 Source Connector 配置文件
```
vi source-demo.properties
```shell
vi source-demo.json
```
输入以下内容：
```ini title="source-demo.properties"
name=TDengineSourceConnector
connector.class=com.taosdata.kafka.connect.source.TDengineSourceConnector
tasks.max=1
connection.url=jdbc:TAOS://127.0.0.1:6030
connection.username=root
connection.password=taosdata
connection.database=test
connection.attempts=3
connection.backoff.ms=5000
topic.prefix=tdengine-source-
poll.interval.ms=1000
fetch.max.rows=100
key.converter=org.apache.kafka.connect.storage.StringConverter
value.converter=org.apache.kafka.connect.storage.StringConverter
```json title="source-demo.json"
{
"name":"TDengineSourceConnector",
"config":{
"connector.class": "com.taosdata.kafka.connect.source.TDengineSourceConnector",
"tasks.max": 1,
"connection.url": "jdbc:TAOS://127.0.0.1:6030",
"connection.username": "root",
"connection.password": "taosdata",
"connection.database": "test",
"connection.attempts": 3,
"connection.backoff.ms": 5000,
"topic.prefix": "tdengine-source",
"poll.interval.ms": 1000,
"fetch.max.rows": 100,
"topic.per.stable": true,
"topic.ignore.db": false,
"out.format": "line",
"key.converter": "org.apache.kafka.connect.storage.StringConverter",
"value.converter": "org.apache.kafka.connect.storage.StringConverter"
}
}
```
### 准备测试数据
......@@ -344,27 +270,27 @@ INSERT INTO d1001 USING meters TAGS('California.SanFrancisco', 2) VALUES('2018-1
使用 TDengine CLI, 执行 SQL 文件。
```
```shell
taos -f prepare-source-data.sql
```
### 创建 Connector 实例
### 创建 Source Connector 实例
```
confluent local services connect connector load TDengineSourceConnector --config source-demo.properties
```shell
curl -X POST -d @source-demo.json http://localhost:8083/connectors -H "Content-Type: application/json"
```
### 查看 topic 数据
使用 kafka-console-consumer 命令行工具监控主题 tdengine-source-test 中的数据。一开始会输出所有历史数据， 往 TDengine 插入两条新的数据之后，kafka-console-consumer 也立即输出了新增的两条数据。 输出数据 InfluxDB line protocol 的格式。
```
kafka-console-consumer --bootstrap-server localhost:9092 --from-beginning --topic tdengine-source-test
```shell
kafka-console-consumer.sh --bootstrap-server localhost:9092 --from-beginning --topic tdengine-source-test-meters
```
输出：
```
```txt
......
meters,location="California.SanFrancisco",groupid=2i32 current=10.3f32,voltage=219i32,phase=0.31f32 1538548685000000000
meters,location="California.SanFrancisco",groupid=2i32 current=12.6f32,voltage=218i32,phase=0.33f32 1538548695000000000
......@@ -373,7 +299,7 @@ meters,location="California.SanFrancisco",groupid=2i32 current=12.6f32,voltage=2
此时会显示所有历史数据。切换到 TDengine CLI， 插入两条新的数据：
```
```sql
USE test;
INSERT INTO d1001 VALUES (now, 13.3, 229, 0.38);
INSERT INTO d1002 VALUES (now, 16.3, 233, 0.22);
......@@ -387,15 +313,15 @@ INSERT INTO d1002 VALUES (now, 16.3, 233, 0.22);
查看当前活跃的 connector：
```
confluent local services connect connector status
```shell
curl http://localhost:8083/connectors
```
如果按照前述操作，此时应有两个活跃的 connector。使用下面的命令 unload：
```
confluent local services connect connector unload TDengineSinkConnector
confluent local services connect connector unload TDengineSourceConnector
```shell
curl -X DELETE http://localhost:8083/connectors/TDengineSinkConnector
curl -X DELETE http://localhost:8083/connectors/TDengineSourceConnector
```
## 配置参考
......@@ -437,20 +363,19 @@ confluent local services connect connector unload TDengineSourceConnector
3. `timestamp.initial`: 数据同步起始时间。格式为'yyyy-MM-dd HH:mm:ss'，若未指定则从指定 DB 中最早的一条记录开始。
4. `poll.interval.ms`: 检查是否有新建或删除的表的时间间隔，单位为 ms。默认为 1000。
5. `fetch.max.rows` : 检索数据库时最大检索条数。 默认为 100。
6. `query.interval.ms`: 从 TDengine 一次读取数据的时间跨度，需要根据表中的数据特征合理配置，避免一次查询的数据量过大或过小；在具体的环境中建议通过测试设置一个较优值，默认值为 1000.
7. `topic.per.stable`: 如果设置为true，表示一个超级表对应一个 Kafka topic，topic的命名规则 `<topic.prefix>-<connection.database>-<stable.name>`；如果设置为 false，则指定的 DB 中的所有数据进入一个 Kafka topic，topic 的命名规则为 `<topic.prefix>-<connection.database>`
6. `query.interval.ms`: 从 TDengine 一次读取数据的时间跨度，需要根据表中的数据特征合理配置，避免一次查询的数据量过大或过小；在具体的环境中建议通过测试设置一个较优值，默认值为 0，即获取到当前最新时间的所有数据。
7. `out.format` : 结果集输出格式。`line` 表示输出格式为 InfluxDB Line 协议格式，`json` 表示输出格式是 json。默认为 line。
8. `topic.per.stable`: 如果设置为 true，表示一个超级表对应一个 Kafka topic，topic的命名规则 `<topic.prefix>-<connection.database>-<stable.name>`；如果设置为 false，则指定的 DB 中的所有数据进入一个 Kafka topic，topic 的命名规则为 `<topic.prefix>-<connection.database>`
9. `topic.ignore.db`: topic 命名规则是否包含 database 名称，true 表示规则为 `<topic.prefix>-<stable.name>`，false 表示规则为 `<topic.prefix>-<connection.database>-<stable.name>`，默认 false。在 `topic.per.stable` 设置为 false 时不生效。
## 其他说明
1. 插件的安装位置可以自定义，请参考官方文档：https://docs.confluent.io/home/connect/self-managed/install.html#install-connector-manually。
2. 本教程的示例程序使用了 Confluent 平台，但是 TDengine Kafka Connector 本身同样适用于独立安装的 Kafka, 且配置方法相同。关于如何在独立安装的 Kafka 环境使用 Kafka Connect 插件， 请参考官方文档： https://kafka.apache.org/documentation/#connect。
1. 关于如何在独立安装的 Kafka 环境使用 Kafka Connect 插件， 请参考官方文档：<https://kafka.apache.org/documentation/#connect>。
## 问题反馈
无论遇到任何问题，都欢迎在本项目的 Github 仓库反馈： https://github.com/taosdata/kafka-connect-tdengine/issues。
无论遇到任何问题，都欢迎在本项目的 Github 仓库反馈：<https://github.com/taosdata/kafka-connect-tdengine/issues>。
## 参考
1. https://www.confluent.io/what-is-apache-kafka
2. https://developer.confluent.io/learn-kafka/kafka-connect/intro
3. https://docs.confluent.io/platform/current/platform.html
1. <https://kafka.apache.org/documentation/>
docs/zh/27-train-faq/01-faq.md
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......@@ -247,10 +247,17 @@ launchctl limit maxfiles
该提示是创建 db 的 vnode 数量不够了，需要的 vnode 不能超过了 dnode 中 vnode 的上限。因为系统默认是一个 dnode 中有 CPU 核数两倍的 vnode，也可以通过配置文件中的参数 supportVnodes 控制。
正常调大 taos.cfg 中 supportVnodes 参数即可。
### 21 【查询】在服务器上的使用 tao-CLI 能查到指定时间段的数据，但在客户端机器上查不到？
### 21 在服务器上的使用 taos-CLI 能查到指定时间段的数据，但在客户端机器上查不到？
这种情况是因为客户端与服务器上设置的时区不一致导致的，调整客户端与服务器的时区一致即可解决。
### 22 【表名】表名确认是存在的，但写入或查询时报表不存在错误，非常奇怪，什么原因？
### 22 表名确认是存在的，但在写入或查询时返回表名不存在，什么原因？
TDengine 中的所有名称，包括数据库名、表名等都是区分大小写的，如果这些名称在程序或 taos-CLI 中没有使用反引号（`）括起来使用，即使你输入的是大写的，引擎也会转化成小写来使用，如果名称前后加上了反引号，引擎就不会再转化成小写，会保持原样来使用。
### 23 在 taos-CLI 中查询，字段内容不能完全显示出来怎么办？
可以使用 \G 参数来竖式显示，如 show databases\G; （为了输入方便，在"\"后加 TAB 键，会自动补全后面的内容）
### 24 使用 taosBenchmark 测试工具写入数据查询很快，为什么我写入的数据查询非常慢？
TDengine 在写入数据时如果有很严重的乱序写入问题，会严重影响查询性能，所以需要在写入前解决乱序的问题。如果业务是从 kafka 消费写入，请合理设计消费者，尽可能的一个子表数据由一个消费者去消费并写入，避免由设计产生的乱序。
### 25 我想统计下前后两条写入记录之间的时间差值是多少？
使用 DIFF 函数，可以查看时间列或数值列前后两条记录的差值，非常方便，详细说明见 SQL手册->函数->DIFF
docs/zh/28-releases/01-tdengine.md
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......@@ -10,6 +10,14 @@ TDengine 2.x 各版本安装包请访问[这里](https://www.taosdata.com/all-do
import Release from "/components/ReleaseV3";
## 3.0.5.0
<Release type="tdengine" version="3.0.5.0" />
## 3.0.4.2
<Release type="tdengine" version="3.0.4.2" />
## 3.0.4.1
<Release type="tdengine" version="3.0.4.1" />
......
docs/zh/28-releases/02-tools.md
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......@@ -10,9 +10,9 @@ taosTools 各版本安装包下载链接如下：
import Release from "/components/ReleaseV3";
## 2.5.0
## 2.5.1
<Release type="tools" version="2.5.0" />
<Release type="tools" version="2.5.1" />
## 2.5.0
......
examples/JDBC/consumer-demo/pom.xml 0 → 100644
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<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.taosdata</groupId>
<artifactId>consumer</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<maven.compiler.source>8</maven.compiler.source>
<maven.compiler.target>8</maven.compiler.target>
</properties>
<dependencies>
<dependency>
<groupId>com.taosdata.jdbc</groupId>
<artifactId>taos-jdbcdriver</artifactId>
<version>3.2.1</version>
</dependency>
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>30.1.1-jre</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-assembly-plugin</artifactId>
<version>3.3.0</version>
<executions>
<execution>
<id>ConsumerDemo</id>
<configuration>
<finalName>ConsumerDemo</finalName>
<archive>
<manifest>
<mainClass>com.taosdata.ConsumerDemo</mainClass>
</manifest>
</archive>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
</configuration>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<configuration>
<source>8</source>
<target>8</target>
<encoding>UTF-8</encoding>
</configuration>
</plugin>
</plugins>
</build>
</project>
\ No newline at end of file
examples/JDBC/consumer-demo/readme.md 0 → 100644
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# How to Run the Consumer Demo Code On Linux OS
TDengine's Consumer demo project is organized in a Maven way so that users can easily compile, package and run the project. If you don't have Maven on your server, you may install it using
```
sudo apt-get install maven
```
## Install TDengine Client and TaosAdapter
Make sure you have already installed a tdengine client on your current develop environment.
Download the tdengine package on our website: ``https://www.taosdata.com/cn/all-downloads/`` and install the client.
## Run Consumer Demo using mvn plugin
run command:
```
mvn clean compile exec:java -Dexec.mainClass="com.taosdata.ConsumerDemo"
```
## Custom configuration
```shell
# the host of TDengine server
export TAOS_HOST="127.0.0.1"
# the port of TDengine server
export TAOS_PORT="6041"
# the consumer type, can be "ws" or "jni"
export TAOS_TYPE="ws"
# the number of consumers
export TAOS_JDBC_CONSUMER_NUM="1"
# the number of processors to consume
export TAOS_JDBC_PROCESSOR_NUM="2"
# the number of records to be consumed per processor per second
export TAOS_JDBC_RATE_PER_PROCESSOR="1000"
# poll wait time in ms
export TAOS_JDBC_POLL_SLEEP="100"
```
## Run Consumer Demo using jar
To compile the demo project, go to the source directory ``TDengine/tests/examples/JDBC/consumer-demo`` and execute
```
mvn clean package assembly:single
```
To run ConsumerDemo.jar, go to ``TDengine/tests/examples/JDBC/consumer-demo`` and execute
```
java -jar target/ConsumerDemo-jar-with-dependencies.jar
```
examples/JDBC/consumer-demo/src/main/java/com/taosdata/Bean.java 0 → 100644
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package com.taosdata;
import java.sql.Timestamp;
public class Bean {
private Timestamp ts;
private Integer c1;
private String c2;
public Timestamp getTs() {
return ts;
}
public void setTs(Timestamp ts) {
this.ts = ts;
}
public Integer getC1() {
return c1;
}
public void setC1(Integer c1) {
this.c1 = c1;
}
public String getC2() {
return c2;
}
public void setC2(String c2) {
this.c2 = c2;
}
@Override
public String toString() {
final StringBuilder sb = new StringBuilder("Bean {");
sb.append("ts=").append(ts);
sb.append(", c1=").append(c1);
sb.append(", c2='").append(c2).append('\'');
sb.append('}');
return sb.toString();
}
}
examples/JDBC/consumer-demo/src/main/java/com/taosdata/BeanDeserializer.java 0 → 100644
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package com.taosdata;
import com.taosdata.jdbc.tmq.ReferenceDeserializer;
public class BeanDeserializer extends ReferenceDeserializer<Bean> {
}
examples/JDBC/consumer-demo/src/main/java/com/taosdata/Config.java 0 → 100644
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package com.taosdata;
public class Config {
public static final String TOPIC = "test_consumer";
public static final String TAOS_HOST = "127.0.0.1";
public static final String TAOS_PORT = "6041";
public static final String TAOS_TYPE = "ws";
public static final int TAOS_JDBC_CONSUMER_NUM = 1;
public static final int TAOS_JDBC_PROCESSOR_NUM = 2;
public static final int TAOS_JDBC_RATE_PER_PROCESSOR = 1000;
public static final int TAOS_JDBC_POLL_SLEEP = 100;
private final int consumerNum;
private final int processCapacity;
private final int rate;
private final int pollSleep;
private final String type;
private final String host;
private final String port;
public Config(String type, String host, String port, int consumerNum, int processCapacity, int rate, int pollSleep) {
this.type = type;
this.consumerNum = consumerNum;
this.processCapacity = processCapacity;
this.rate = rate;
this.pollSleep = pollSleep;
this.host = host;
this.port = port;
}
public int getConsumerNum() {
return consumerNum;
}
public int getProcessCapacity() {
return processCapacity;
}
public int getRate() {
return rate;
}
public int getPollSleep() {
return pollSleep;
}
public String getHost() {
return host;
}
public String getPort() {
return port;
}
public String getType() {
return type;
}
public static Config getFromENV() {
String host = System.getenv("TAOS_HOST") != null ? System.getenv("TAOS_HOST") : TAOS_HOST;
String port = System.getenv("TAOS_PORT") != null ? System.getenv("TAOS_PORT") : TAOS_PORT;
String type = System.getenv("TAOS_TYPE") != null ? System.getenv("TAOS_TYPE") : TAOS_TYPE;
String c = System.getenv("TAOS_JDBC_CONSUMER_NUM");
int num = c != null ? Integer.parseInt(c) : TAOS_JDBC_CONSUMER_NUM;
String p = System.getenv("TAOS_JDBC_PROCESSOR_NUM");
int capacity = p != null ? Integer.parseInt(p) : TAOS_JDBC_PROCESSOR_NUM;
String r = System.getenv("TAOS_JDBC_RATE_PER_PROCESSOR");
int rate = r != null ? Integer.parseInt(r) : TAOS_JDBC_RATE_PER_PROCESSOR;
String s = System.getenv("TAOS_JDBC_POLL_SLEEP");
int sleep = s != null ? Integer.parseInt(s) : TAOS_JDBC_POLL_SLEEP;
return new Config(type, host, port, num, capacity, rate, sleep);
}
}
examples/JDBC/consumer-demo/src/main/java/com/taosdata/ConsumerDemo.java 0 → 100644
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package com.taosdata;
import com.taosdata.jdbc.tmq.TMQConstants;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;
import java.sql.Statement;
import java.util.Properties;
import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicInteger;
import static com.taosdata.Config.*;
public class ConsumerDemo {
public static void main(String[] args) throws SQLException {
// Config
Config config = Config.getFromENV();
// Generated data
mockData();
Properties prop = new Properties();
prop.setProperty(TMQConstants.CONNECT_TYPE, config.getType());
prop.setProperty(TMQConstants.BOOTSTRAP_SERVERS, config.getHost() + ":" + config.getPort());
prop.setProperty(TMQConstants.CONNECT_USER, "root");
prop.setProperty(TMQConstants.CONNECT_PASS, "taosdata");
prop.setProperty(TMQConstants.MSG_WITH_TABLE_NAME, "true");
prop.setProperty(TMQConstants.ENABLE_AUTO_COMMIT, "true");
prop.setProperty(TMQConstants.GROUP_ID, "gId");
prop.setProperty(TMQConstants.VALUE_DESERIALIZER, "com.taosdata.BeanDeserializer");
for (int i = 0; i < config.getConsumerNum() - 1; i++) {
new Thread(new Worker(prop, config)).start();
}
new Worker(prop, config).run();
}
public static void mockData() throws SQLException {
String dbName = "test_consumer";
String tableName = "st";
String url = "jdbc:TAOS-RS://" + TAOS_HOST + ":" + TAOS_PORT + "/?user=root&password=taosdata&batchfetch=true";
Connection connection = DriverManager.getConnection(url);
Statement statement = connection.createStatement();
statement.executeUpdate("create database if not exists " + dbName + " WAL_RETENTION_PERIOD 3650");
statement.executeUpdate("use " + dbName);
statement.executeUpdate("create table if not exists " + tableName + " (ts timestamp, c1 int, c2 nchar(100)) ");
statement.executeUpdate("create topic if not exists " + TOPIC + " as select ts, c1, c2 from " + tableName);
ScheduledExecutorService scheduledExecutorService = Executors.newSingleThreadScheduledExecutor(r -> {
Thread t = new Thread(r);
t.setName("mock-data-thread-" + t.getId());
return t;
});
AtomicInteger atomic = new AtomicInteger();
scheduledExecutorService.scheduleWithFixedDelay(() -> {
int i = atomic.getAndIncrement();
try {
statement.executeUpdate("insert into " + tableName + " values(now, " + i + ",'" + i + "')");
} catch (SQLException e) {
// ignore
}
}, 0, 10, TimeUnit.MILLISECONDS);
}
}
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package com.taosdata;
import com.google.common.util.concurrent.RateLimiter;
import com.taosdata.jdbc.tmq.ConsumerRecord;
import com.taosdata.jdbc.tmq.ConsumerRecords;
import com.taosdata.jdbc.tmq.TaosConsumer;
import java.sql.SQLException;
import java.time.Duration;
import java.time.LocalDateTime;
import java.util.Collections;
import java.util.Properties;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.Semaphore;
public class Worker implements Runnable {
int sleepTime;
int rate;
ForkJoinPool pool = new ForkJoinPool();
Semaphore semaphore;
TaosConsumer<Bean> consumer;
public Worker(Properties prop, Config config) throws SQLException {
consumer = new TaosConsumer<>(prop);
consumer.subscribe(Collections.singletonList(Config.TOPIC));
semaphore = new Semaphore(config.getProcessCapacity());
sleepTime = config.getPollSleep();
rate = config.getRate();
}
@Override
public void run() {
while (!Thread.interrupted()) {
try {
// 控制请求频率
if (semaphore.tryAcquire()) {
ConsumerRecords<Bean> records = consumer.poll(Duration.ofMillis(sleepTime));
pool.submit(() -> {
RateLimiter limiter = RateLimiter.create(rate);
try {
for (ConsumerRecord<Bean> record : records) {
// 流量控制
limiter.acquire();
// 业务处理数据
System.out.println("[" + LocalDateTime.now() + "] Thread id:" + Thread.currentThread().getId() + " -> " + record.value());
}
} finally {
semaphore.release();
}
});
}
} catch (SQLException e) {
e.printStackTrace();
}
}
}
}
examples/JDBC/springbootdemo/src/main/resources/application.properties
浏览文件 @ 3689b41f
......@@ -5,7 +5,7 @@
#spring.datasource.password=taosdata
# datasource config - JDBC-RESTful
spring.datasource.driver-class-name=com.taosdata.jdbc.rs.RestfulDriver
spring.datasource.url=jdbc:TAOS-RS://localhost:6041/test?timezone=UTC-8&charset=UTF-8&locale=en_US.UTF-8
spring.datasource.url=jdbc:TAOS-RS://localhost:6041/test
spring.datasource.username=root
spring.datasource.password=taosdata
spring.datasource.druid.initial-size=5
......
examples/c/CMakeLists.txt
浏览文件 @ 3689b41f
......@@ -42,27 +42,27 @@ IF (TD_LINUX)
)
target_link_libraries(tmq
taos_static
taos
)
target_link_libraries(stream_demo
taos_static
taos
)
target_link_libraries(schemaless
taos_static
taos
)
target_link_libraries(prepare
taos_static
taos
)
target_link_libraries(demo
taos_static
taos
)
target_link_libraries(asyncdemo
taos_static
taos
)
SET_TARGET_PROPERTIES(tmq PROPERTIES OUTPUT_NAME tmq)
......
examples/lua/lua51/lua_connector51.c
浏览文件 @ 3689b41f
......@@ -162,6 +162,7 @@ static int l_query(lua_State *L){
case TSDB_DATA_TYPE_JSON:
case TSDB_DATA_TYPE_BINARY:
case TSDB_DATA_TYPE_NCHAR:
case TSDB_DATA_TYPE_GEOMETRY:
//printf("type:%d, max len:%d, current len:%d\n",fields[i].type, fields[i].bytes, length[i]);
lua_pushlstring(L,(char *)row[i], length[i]);
break;
......
examples/lua/lua_connector.c
浏览文件 @ 3689b41f
......@@ -161,6 +161,7 @@ static int l_query(lua_State *L){
case TSDB_DATA_TYPE_JSON:
case TSDB_DATA_TYPE_BINARY:
case TSDB_DATA_TYPE_NCHAR:
case TSDB_DATA_TYPE_GEOMETRY:
//printf("type:%d, max len:%d, current len:%d\n",fields[i].type, fields[i].bytes, length[i]);
lua_pushlstring(L,(char *)row[i], length[i]);
break;
......
include/client/taos.h
浏览文件 @ 3689b41f
......@@ -51,7 +51,8 @@ typedef void TAOS_SUB;
#define TSDB_DATA_TYPE_BLOB 18 // binary
#define TSDB_DATA_TYPE_MEDIUMBLOB 19
#define TSDB_DATA_TYPE_BINARY TSDB_DATA_TYPE_VARCHAR // string
#define TSDB_DATA_TYPE_MAX 20
#define TSDB_DATA_TYPE_GEOMETRY 20 // geometry
#define TSDB_DATA_TYPE_MAX 21
typedef enum {
TSDB_OPTION_LOCALE,
......
include/common/tcommon.h
浏览文件 @ 3689b41f
......@@ -37,6 +37,13 @@ extern "C" {
)
// clang-format on
typedef bool (*state_key_cmpr_fn)(void* pKey1, void* pKey2);
typedef struct STableKeyInfo {
uint64_t uid;
uint64_t groupId;
} STableKeyInfo;
typedef struct SWinKey {
uint64_t groupId;
TSKEY ts;
......@@ -224,6 +231,7 @@ typedef struct SColumnInfoData {
};
SColumnInfo info; // column info
bool hasNull; // if current column data has null value.
bool reassigned; // if current column data is reassigned.
} SColumnInfoData;
typedef struct SQueryTableDataCond {
......
include/common/tdatablock.h
浏览文件 @ 3689b41f
......@@ -178,6 +178,7 @@ int32_t getJsonValueLen(const char* data);
int32_t colDataSetVal(SColumnInfoData* pColumnInfoData, uint32_t rowIndex, const char* pData, bool isNull);
int32_t colDataAppend(SColumnInfoData* pColumnInfoData, uint32_t rowIndex, const char* pData, bool isNull);
int32_t colDataReassignVal(SColumnInfoData* pColumnInfoData, uint32_t dstRowIdx, uint32_t srcRowIdx, const char* pData);
int32_t colDataSetNItems(SColumnInfoData* pColumnInfoData, uint32_t rowIndex, const char* pData, uint32_t numOfRows, bool trimValue);
int32_t colDataMergeCol(SColumnInfoData* pColumnInfoData, int32_t numOfRow1, int32_t* capacity,
const SColumnInfoData* pSource, int32_t numOfRow2);
......@@ -247,6 +248,7 @@ int32_t buildSubmitReqFromDataBlock(SSubmitReq2** pReq, const SSDataBlock* pData
tb_uid_t suid);
char* buildCtbNameByGroupId(const char* stbName, uint64_t groupId);
int32_t buildCtbNameByGroupIdImpl(const char* stbName, uint64_t groupId, char* pBuf);
static FORCE_INLINE int32_t blockGetEncodeSize(const SSDataBlock* pBlock) {
return blockDataGetSerialMetaSize(taosArrayGetSize(pBlock->pDataBlock)) + blockDataGetSize(pBlock);
......
include/common/tdataformat.h
浏览文件 @ 3689b41f
......@@ -145,7 +145,7 @@ int32_t tColDataCopy(SColData *pColDataFrom, SColData *pColData, xMallocFn xMall
extern void (*tColDataCalcSMA[])(SColData *pColData, int64_t *sum, int64_t *max, int64_t *min, int16_t *numOfNull);
// for stmt bind
int32_t tColDataAddValueByBind(SColData *pColData, TAOS_MULTI_BIND *pBind);
int32_t tColDataAddValueByBind(SColData *pColData, TAOS_MULTI_BIND *pBind, int32_t buffMaxLen);
void tColDataSortMerge(SArray *colDataArr);
// for raw block
......
include/common/tglobal.h
浏览文件 @ 3689b41f
......@@ -29,7 +29,6 @@ extern "C" {
#define SLOW_LOG_TYPE_OTHERS 0x4
#define SLOW_LOG_TYPE_ALL 0xFFFFFFFF
// cluster
extern char tsFirst[];
extern char tsSecond[];
......@@ -83,6 +82,7 @@ extern int64_t tsVndCommitMaxIntervalMs;
// mnode
extern int64_t tsMndSdbWriteDelta;
extern int64_t tsMndLogRetention;
extern bool tsMndSkipGrant;
// monitor
extern bool tsEnableMonitor;
......@@ -131,7 +131,7 @@ extern int32_t tsSlowLogScope;
// client
extern int32_t tsMinSlidingTime;
extern int32_t tsMinIntervalTime;
extern int32_t tsMaxMemUsedByInsert;
extern int32_t tsMaxInsertBatchRows;
// build info
extern char version[];
......@@ -180,6 +180,8 @@ extern int32_t tsRpcRetryInterval;
extern bool tsDisableStream;
extern int64_t tsStreamBufferSize;
extern int64_t tsCheckpointInterval;
extern bool tsFilterScalarMode;
extern int32_t tsMaxStreamBackendCache;
// #define NEEDTO_COMPRESSS_MSG(size) (tsCompressMsgSize != -1 && (size) > tsCompressMsgSize)
......
include/common/tmsg.h
浏览文件 @ 3689b41f
......@@ -2009,10 +2009,8 @@ typedef struct {
int8_t withMeta;
char* sql;
char subDbName[TSDB_DB_FNAME_LEN];
union {
char* ast;
char subStbName[TSDB_TABLE_FNAME_LEN];
};
char* ast;
char subStbName[TSDB_TABLE_FNAME_LEN];
} SCMCreateTopicReq;
int32_t tSerializeSCMCreateTopicReq(void* buf, int32_t bufLen, const SCMCreateTopicReq* pReq);
......@@ -2809,37 +2807,49 @@ typedef struct {
int64_t suid;
} SMqRebVgReq;
static FORCE_INLINE int32_t tEncodeSMqRebVgReq(void** buf, const SMqRebVgReq* pReq) {
int32_t tlen = 0;
tlen += taosEncodeFixedI64(buf, pReq->leftForVer);
tlen += taosEncodeFixedI32(buf, pReq->vgId);
tlen += taosEncodeFixedI64(buf, pReq->oldConsumerId);
tlen += taosEncodeFixedI64(buf, pReq->newConsumerId);
tlen += taosEncodeString(buf, pReq->subKey);
tlen += taosEncodeFixedI8(buf, pReq->subType);
tlen += taosEncodeFixedI8(buf, pReq->withMeta);
static FORCE_INLINE int tEncodeSMqRebVgReq(SEncoder *pCoder, const SMqRebVgReq* pReq) {
if (tStartEncode(pCoder) < 0) return -1;
if (tEncodeI64(pCoder, pReq->leftForVer) < 0) return -1;
if (tEncodeI32(pCoder, pReq->vgId) < 0) return -1;
if (tEncodeI64(pCoder, pReq->oldConsumerId) < 0) return -1;
if (tEncodeI64(pCoder, pReq->newConsumerId) < 0) return -1;
if (tEncodeCStr(pCoder, pReq->subKey) < 0) return -1;
if (tEncodeI8(pCoder, pReq->subType) < 0) return -1;
if (tEncodeI8(pCoder, pReq->withMeta) < 0) return -1;
if (pReq->subType == TOPIC_SUB_TYPE__COLUMN) {
tlen += taosEncodeString(buf, pReq->qmsg);
if (tEncodeCStr(pCoder, pReq->qmsg) < 0) return -1;
} else if (pReq->subType == TOPIC_SUB_TYPE__TABLE) {
tlen += taosEncodeFixedI64(buf, pReq->suid);
if (tEncodeI64(pCoder, pReq->suid) < 0) return -1;
if (tEncodeCStr(pCoder, pReq->qmsg) < 0) return -1;
}
return tlen;
tEndEncode(pCoder);
return 0;
}
static FORCE_INLINE void* tDecodeSMqRebVgReq(const void* buf, SMqRebVgReq* pReq) {
buf = taosDecodeFixedI64(buf, &pReq->leftForVer);
buf = taosDecodeFixedI32(buf, &pReq->vgId);
buf = taosDecodeFixedI64(buf, &pReq->oldConsumerId);
buf = taosDecodeFixedI64(buf, &pReq->newConsumerId);
buf = taosDecodeStringTo(buf, pReq->subKey);
buf = taosDecodeFixedI8(buf, &pReq->subType);
buf = taosDecodeFixedI8(buf, &pReq->withMeta);
static FORCE_INLINE int tDecodeSMqRebVgReq(SDecoder *pCoder, SMqRebVgReq* pReq) {
if (tStartDecode(pCoder) < 0) return -1;
if (tDecodeI64(pCoder, &pReq->leftForVer) < 0) return -1;
if (tDecodeI32(pCoder, &pReq->vgId) < 0) return -1;
if (tDecodeI64(pCoder, &pReq->oldConsumerId) < 0) return -1;
if (tDecodeI64(pCoder, &pReq->newConsumerId) < 0) return -1;
if (tDecodeCStrTo(pCoder, pReq->subKey) < 0) return -1;
if (tDecodeI8(pCoder, &pReq->subType) < 0) return -1;
if (tDecodeI8(pCoder, &pReq->withMeta) < 0) return -1;
if (pReq->subType == TOPIC_SUB_TYPE__COLUMN) {
buf = taosDecodeString(buf, &pReq->qmsg);
if (tDecodeCStr(pCoder, &pReq->qmsg) < 0) return -1;
} else if (pReq->subType == TOPIC_SUB_TYPE__TABLE) {
buf = taosDecodeFixedI64(buf, &pReq->suid);
if (tDecodeI64(pCoder, &pReq->suid) < 0) return -1;
if (!tDecodeIsEnd(pCoder)){
if (tDecodeCStr(pCoder, &pReq->qmsg) < 0) return -1;
}
}
return (void*)buf;
tEndDecode(pCoder);
return 0;
}
typedef struct {
......
include/common/ttime.h
浏览文件 @ 3689b41f
......@@ -23,7 +23,7 @@
extern "C" {
#endif
#define TIME_IS_VAR_DURATION(_t) ((_t) == 'n' || (_t) == 'y' || (_t) == 'N' || (_t) == 'Y')
#define IS_CALENDAR_TIME_DURATION(_t) ((_t) == 'n' || (_t) == 'y' || (_t) == 'N' || (_t) == 'Y')
#define TIME_UNIT_NANOSECOND 'b'
#define TIME_UNIT_MICROSECOND 'u'
......@@ -74,7 +74,7 @@ static FORCE_INLINE int64_t taosGetTimestampToday(int32_t precision) {
int64_t taosTimeAdd(int64_t t, int64_t duration, char unit, int32_t precision);
int64_t taosTimeTruncate(int64_t t, const SInterval* pInterval, int32_t precision);
int64_t taosTimeTruncate(int64_t ts, const SInterval* pInterval);
int32_t taosTimeCountInterval(int64_t skey, int64_t ekey, int64_t interval, char unit, int32_t precision);
int32_t parseAbsoluteDuration(const char* token, int32_t tokenlen, int64_t* ts, char* unit, int32_t timePrecision);
......
include/common/ttokendef.h
浏览文件 @ 3689b41f
此差异已折叠。
include/common/ttypes.h
浏览文件 @ 3689b41f
......@@ -269,7 +269,7 @@ typedef struct {
(IS_NUMERIC_TYPE(_t) || (_t) == (TSDB_DATA_TYPE_BOOL) || (_t) == (TSDB_DATA_TYPE_TIMESTAMP))
#define IS_VAR_DATA_TYPE(t) \
(((t) == TSDB_DATA_TYPE_VARCHAR) || ((t) == TSDB_DATA_TYPE_NCHAR) || ((t) == TSDB_DATA_TYPE_JSON))
(((t) == TSDB_DATA_TYPE_VARCHAR) || ((t) == TSDB_DATA_TYPE_NCHAR) || ((t) == TSDB_DATA_TYPE_JSON) || ((t) == TSDB_DATA_TYPE_GEOMETRY))
#define IS_STR_DATA_TYPE(t) (((t) == TSDB_DATA_TYPE_VARCHAR) || ((t) == TSDB_DATA_TYPE_NCHAR))
#define IS_VALID_TINYINT(_t) ((_t) >= INT8_MIN && (_t) <= INT8_MAX)
......@@ -316,6 +316,8 @@ static FORCE_INLINE bool isNull(const void *val, int32_t type) {
return *(uint32_t *)val == TSDB_DATA_UINT_NULL;
case TSDB_DATA_TYPE_UBIGINT:
return *(uint64_t *)val == TSDB_DATA_UBIGINT_NULL;
case TSDB_DATA_TYPE_GEOMETRY:
return varDataLen(val) == sizeof(int8_t) && *(uint8_t *)varDataVal(val) == TSDB_DATA_GEOMETRY_NULL;
default:
return false;
......
include/libs/executor/dataSinkMgt.h
浏览文件 @ 3689b41f
......@@ -59,7 +59,7 @@ typedef struct SDataSinkMgtCfg {
uint32_t maxDataBlockNumPerQuery;
} SDataSinkMgtCfg;
int32_t dsDataSinkMgtInit(SDataSinkMgtCfg* cfg);
int32_t dsDataSinkMgtInit(SDataSinkMgtCfg* cfg, SStorageAPI* pAPI);
typedef struct SInputData {
const struct SSDataBlock* pData;
......
include/libs/executor/executor.h
浏览文件 @ 3689b41f
......@@ -23,6 +23,7 @@ extern "C" {
#include "query.h"
#include "tcommon.h"
#include "tmsgcb.h"
#include "storageapi.h"
typedef void* qTaskInfo_t;
typedef void* DataSinkHandle;
......@@ -41,7 +42,6 @@ typedef struct {
typedef struct {
void* tqReader;
void* meta;
void* config;
void* vnode;
void* mnd;
......@@ -51,10 +51,10 @@ typedef struct {
bool initTableReader;
bool initTqReader;
int32_t numOfVgroups;
void* sContext; // SSnapContext*
void* sContext; // SSnapContext*
void* pStateBackend;
void* pStateBackend;
struct SStorageAPI api;
} SReadHandle;
// in queue mode, data streams are seperated by msg
......@@ -82,6 +82,8 @@ qTaskInfo_t qCreateStreamExecTaskInfo(void* msg, SReadHandle* readers, int32_t v
qTaskInfo_t qCreateQueueExecTaskInfo(void* msg, SReadHandle* pReaderHandle, int32_t vgId, int32_t* numOfCols,
uint64_t id);
int32_t qGetTableList(int64_t suid, void* pVnode, void* node, SArray **tableList, void* pTaskInfo);
/**
* set the task Id, usually used by message queue process
* @param tinfo
......@@ -90,6 +92,8 @@ qTaskInfo_t qCreateQueueExecTaskInfo(void* msg, SReadHandle* pReaderHandle, int3
*/
void qSetTaskId(qTaskInfo_t tinfo, uint64_t taskId, uint64_t queryId);
//void qSetTaskCode(qTaskInfo_t tinfo, int32_t code);
int32_t qSetStreamOpOpen(qTaskInfo_t tinfo);
// todo refactor
......@@ -186,7 +190,17 @@ int32_t qSerializeTaskStatus(qTaskInfo_t tinfo, char** pOutput, int32_t* len);
int32_t qDeserializeTaskStatus(qTaskInfo_t tinfo, const char* pInput, int32_t len);
STimeWindow getAlignQueryTimeWindow(SInterval* pInterval, int32_t precision, int64_t key);
void getNextTimeWindow(const SInterval* pInterval, STimeWindow* tw, int32_t order);
void getInitialStartTimeWindow(SInterval* pInterval, TSKEY ts, STimeWindow* w, bool ascQuery);
STimeWindow getAlignQueryTimeWindow(const SInterval* pInterval, int64_t key);
/**
* return the scan info, in the form of tuple of two items, including table uid and current timestamp
* @param tinfo
* @param uid
* @param ts
* @return
*/
int32_t qGetStreamScanStatus(qTaskInfo_t tinfo, uint64_t* uid, int64_t* ts);
SArray* qGetQueriedTableListInfo(qTaskInfo_t tinfo);
......
include/libs/executor/storageapi.h 0 → 100644
浏览文件 @ 3689b41f
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include/libs/function/function.h
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include/libs/function/functionMgt.h
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include/libs/function/taosudf.h
浏览文件 @ 3689b41f
......@@ -109,7 +109,7 @@ typedef uint16_t VarDataLenT; // maxVarDataLen: 65535
#define varDataLenByData(v) (*(VarDataLenT *)(((char *)(v)) - VARSTR_HEADER_SIZE))
#define varDataSetLen(v, _len) (((VarDataLenT *)(v))[0] = (VarDataLenT)(_len))
#define IS_VAR_DATA_TYPE(t) \
(((t) == TSDB_DATA_TYPE_VARCHAR) || ((t) == TSDB_DATA_TYPE_NCHAR) || ((t) == TSDB_DATA_TYPE_JSON))
(((t) == TSDB_DATA_TYPE_VARCHAR) || ((t) == TSDB_DATA_TYPE_NCHAR) || ((t) == TSDB_DATA_TYPE_JSON) || ((t) == TSDB_DATA_TYPE_GEOMETRY))
#define IS_STR_DATA_TYPE(t) (((t) == TSDB_DATA_TYPE_VARCHAR) || ((t) == TSDB_DATA_TYPE_NCHAR))
static FORCE_INLINE char *udfColDataGetData(const SUdfColumn *pColumn, int32_t row) {
......
include/libs/geometry/geomFunc.h 0 → 100644
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include/libs/geometry/geosWrapper.h 0 → 100644
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include/libs/index/index.h
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include/libs/nodes/cmdnodes.h
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include/libs/nodes/nodes.h
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include/libs/nodes/plannodes.h
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include/libs/nodes/querynodes.h
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include/libs/qcom/query.h
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include/libs/stream/streamState.h
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include/libs/stream/tstream.h
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include/libs/stream/tstreamUpdate.h
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include/libs/wal/wal.h
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include/os/osMemory.h
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include/util/taoserror.h
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include/util/tdef.h
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packaging/docker/dockerbuild.sh
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packaging/tools/makeclient.sh
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source/common/src/tdatablock.c
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source/common/src/ttszip.c
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source/dnode/mnode/impl/src/mndDb.c
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source/dnode/vnode/CMakeLists.txt
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