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TDengine

taosdata / TDengine
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TDengine
TDengine
提交 d093b0e2 编写于 作者: K kailixu
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chore: merge 3.0

上级 9faefb74 9b3e34d5
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.gitignore
浏览文件 @ d093b0e2
......@@ -16,7 +16,6 @@ debug/
release/
target/
debs/
deps/
rpms/
mac/
*.pyc
......@@ -131,3 +130,4 @@ tools/BUGS
tools/taos-tools
tools/taosws-rs
tags
.clangd
.pre-commit-config.yaml 0 → 100644
浏览文件 @ d093b0e2
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v2.3.0
hooks:
- id: check-yaml
- id: check-json
- id: end-of-file-fixer
- id: trailing-whitespace
repos:
- repo: https://github.com/psf/black
rev: stable
hooks:
- id: black
repos:
- repo: https://github.com/pocc/pre-commit-hooks
rev: master
hooks:
- id: cppcheck
args: ["--error-exitcode=0"]
repos:
- repo: https://github.com/crate-ci/typos
rev: v1.15.7
hooks:
- id: typos
CMakeLists.txt
浏览文件 @ d093b0e2
......@@ -15,11 +15,15 @@ SET(TD_COMMUNITY_DIR ${PROJECT_SOURCE_DIR})
set(TD_SUPPORT_DIR "${TD_SOURCE_DIR}/cmake")
set(TD_CONTRIB_DIR "${TD_SOURCE_DIR}/contrib")
include(${TD_SUPPORT_DIR}/cmake.platform)
include(${TD_SUPPORT_DIR}/cmake.define)
include(${TD_SUPPORT_DIR}/cmake.options)
include(${TD_SUPPORT_DIR}/cmake.version)
# contrib
add_subdirectory(contrib)
......
CONTRIBUTING-CN.md
浏览文件 @ d093b0e2
......@@ -18,7 +18,7 @@
注意：修改文档的分支要以`docs/`为开头，以免进行不必要的测试。
4. 创建pull request，将自己的分支合并到开发分支`3.0`，我们开发团队将尽快审核。
如遇任何问题，请添加官方微信TDengineECO。我们的团队会帮忙解决。
如遇任何问题，请添加官方微信 tdengine1。我们的团队会帮忙解决。
## 给贡献者的礼品
......@@ -48,4 +48,4 @@ TDengine 社区致力于让更多的开发者理解和使用它。
## 联系我们
如果您有什么问题需要解决，或者有什么问题需要解答，可以添加微信：TDengineECO
如果您有什么问题需要解决，或者有什么问题需要解答，可以添加微信：tdengine1。
Jenkinsfile2
浏览文件 @ d093b0e2
......@@ -314,7 +314,7 @@ def pre_test_build_win() {
cd %WIN_CONNECTOR_ROOT%
python.exe -m pip install --upgrade pip
python -m pip uninstall taospy -y
python -m pip install taospy==2.7.6
python -m pip install taospy==2.7.10
xcopy /e/y/i/f %WIN_INTERNAL_ROOT%\\debug\\build\\lib\\taos.dll C:\\Windows\\System32
'''
return 1
......
README-CN.md
浏览文件 @ d093b0e2
......@@ -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
......@@ -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 gflags git openssl-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++ gflags make cmake epel-release git openssl-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 gflags pkgconfig
```
### 设置 golang 开发环境
......
README.md
浏览文件 @ d093b0e2
......@@ -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 gflags git openssl-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 gflags git openssl-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 gflags pkgconfig
```
### Setup golang environment
......
cmake/cmake.define
浏览文件 @ d093b0e2
cmake_minimum_required(VERSION 3.0)
set(CMAKE_VERBOSE_MAKEFILE OFF)
set(CMAKE_VERBOSE_MAKEFILE ON)
set(TD_BUILD_TAOSA_INTERNAL FALSE)
#set output directory
......@@ -115,15 +115,6 @@ ELSE ()
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${GCC_COVERAGE_COMPILE_FLAGS} ${GCC_COVERAGE_LINK_FLAGS}")
ENDIF ()
IF (${BUILD_SANITIZER})
SET(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Werror -Werror=return-type -fPIC -gdwarf-2 -fsanitize=address -fsanitize=undefined -fsanitize-recover=all -fsanitize=float-divide-by-zero -fsanitize=float-cast-overflow -fno-sanitize=shift-base -fno-sanitize=alignment -g3 -Wformat=0")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Werror -Wno-literal-suffix -Werror=return-type -fPIC -gdwarf-2 -fsanitize=address -fsanitize=undefined -fsanitize-recover=all -fsanitize=float-divide-by-zero -fsanitize=float-cast-overflow -fno-sanitize=shift-base -fno-sanitize=alignment -g3 -Wformat=0")
MESSAGE(STATUS "Compile with Address Sanitizer!")
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} -Werror -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")
ENDIF ()
# disable all assert
IF ((${DISABLE_ASSERT} MATCHES "true") OR (${DISABLE_ASSERTS} MATCHES "true"))
ADD_DEFINITIONS(-DDISABLE_ASSERT)
......@@ -165,4 +156,20 @@ ELSE ()
MESSAGE(STATUS "SIMD instructions (FMA/AVX/AVX2) is ACTIVATED")
ENDIF()
# build mode
SET(CMAKE_C_FLAGS_REL "${CMAKE_C_FLAGS} -Werror -Werror=return-type -fPIC -O3 -Wformat=2 -Wno-format-nonliteral -Wno-format-truncation -Wno-format-y2k")
SET(CMAKE_CXX_FLAGS_REL "${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")
IF (${BUILD_SANITIZER})
SET(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Werror -Werror=return-type -fPIC -gdwarf-2 -fsanitize=address -fsanitize=undefined -fsanitize-recover=all -fsanitize=float-divide-by-zero -fsanitize=float-cast-overflow -fno-sanitize=shift-base -fno-sanitize=alignment -g3 -Wformat=0")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-literal-suffix -Werror=return-type -fPIC -gdwarf-2 -fsanitize=address -fsanitize=undefined -fsanitize-recover=all -fsanitize=float-divide-by-zero -fsanitize=float-cast-overflow -fno-sanitize=shift-base -fno-sanitize=alignment -g3 -Wformat=0")
MESSAGE(STATUS "Compile with Address Sanitizer!")
ELSEIF (${BUILD_RELEASE})
SET(CMAKE_C_FLAGS "${CMAKE_C_FLAGS_REL}")
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS_REL}")
ELSE ()
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 ()
ENDIF ()
cmake/cmake.options
浏览文件 @ d093b0e2
......@@ -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
""
......@@ -109,7 +122,7 @@ option(
option(
BUILD_WITH_ROCKSDB
"If build with rocksdb"
OFF
ON
)
option(
......@@ -171,3 +184,14 @@ option(
ON
)
option(
BUILD_RELEASE
"If build release version"
OFF
)
option(
BUILD_CONTRIB
"If build thirdpart from source"
OFF
)
cmake/cmake.platform
浏览文件 @ d093b0e2
......@@ -121,6 +121,12 @@ IF ("${CPUTYPE}" STREQUAL "")
SET(TD_LOONGARCH_64 TRUE)
ADD_DEFINITIONS("-D_TD_LOONGARCH_")
ADD_DEFINITIONS("-D_TD_LOONGARCH_64")
ELSEIF (CMAKE_SYSTEM_PROCESSOR MATCHES "mips64")
SET(PLATFORM_ARCH_STR "mips")
MESSAGE(STATUS "input cpuType: mips64")
SET(TD_MIPS_64 TRUE)
ADD_DEFINITIONS("-D_TD_MIPS_")
ADD_DEFINITIONS("-D_TD_MIPS_64")
ENDIF ()
ELSE ()
# if generate ARM version:
......@@ -162,7 +168,27 @@ ELSE ()
ENDIF ()
ENDIF ()
IF(APPLE)
set(CMAKE_THREAD_LIBS_INIT "-lpthread")
set(CMAKE_HAVE_THREADS_LIBRARY 1)
set(CMAKE_USE_WIN32_THREADS_INIT 0)
set(CMAKE_USE_PTHREADS 1)
set(THREADS_PREFER_PTHREAD_FLAG ON)
ENDIF()
MESSAGE(STATUS "Platform arch:" ${PLATFORM_ARCH_STR})
set(TD_DEPS_DIR "x86")
if (TD_LINUX)
IF (TD_ARM_64 OR TD_ARM_32)
set(TD_DEPS_DIR "arm")
ELSEIF (TD_MIPS_64)
set(TD_DEPS_DIR "mips")
ELSE()
set(TD_DEPS_DIR "x86")
ENDIF()
endif()
MESSAGE(STATUS "DEPS_DIR: " ${TD_DEPS_DIR})
MESSAGE("C Compiler: ${CMAKE_C_COMPILER} (${CMAKE_C_COMPILER_ID}, ${CMAKE_C_COMPILER_VERSION})")
MESSAGE("CXX Compiler: ${CMAKE_CXX_COMPILER} (${CMAKE_C_COMPILER_ID}, ${CMAKE_CXX_COMPILER_VERSION})")
cmake/cmake.version
浏览文件 @ d093b0e2
......@@ -2,7 +2,7 @@
IF (DEFINED VERNUMBER)
SET(TD_VER_NUMBER ${VERNUMBER})
ELSE ()
SET(TD_VER_NUMBER "3.0.4.1")
SET(TD_VER_NUMBER "3.1.0.0.alpha")
ENDIF ()
IF (DEFINED VERCOMPATIBLE)
......
cmake/geos_CMakeLists.txt.in 0 → 100644
浏览文件 @ d093b0e2
# geos
ExternalProject_Add(geos
GIT_REPOSITORY https://github.com/libgeos/geos.git
GIT_TAG 3.12.0
SOURCE_DIR "${TD_CONTRIB_DIR}/geos"
BINARY_DIR ""
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
cmake/rocksdb_CMakeLists.txt.in
浏览文件 @ d093b0e2
# rocksdb
ExternalProject_Add(rocksdb
GIT_REPOSITORY https://github.com/taosdata-contrib/rocksdb.git
GIT_TAG v6.23.3
SOURCE_DIR "${TD_CONTRIB_DIR}/rocksdb"
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
\ No newline at end of file
if (${BUILD_CONTRIB})
ExternalProject_Add(rocksdb
URL https://github.com/facebook/rocksdb/archive/refs/tags/v8.1.1.tar.gz
URL_HASH MD5=3b4c97ee45df9c8a5517308d31ab008b
DOWNLOAD_NO_PROGRESS 1
DOWNLOAD_DIR "${TD_CONTRIB_DIR}/deps-download"
SOURCE_DIR "${TD_CONTRIB_DIR}/rocksdb"
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
else()
if (NOT ${TD_LINUX})
ExternalProject_Add(rocksdb
URL https://github.com/facebook/rocksdb/archive/refs/tags/v8.1.1.tar.gz
URL_HASH MD5=3b4c97ee45df9c8a5517308d31ab008b
DOWNLOAD_NO_PROGRESS 1
DOWNLOAD_DIR "${TD_CONTRIB_DIR}/deps-download"
SOURCE_DIR "${TD_CONTRIB_DIR}/rocksdb"
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
endif()
endif()
cmake/stub_CMakeLists.txt.in
浏览文件 @ d093b0e2
......@@ -2,6 +2,7 @@
# stub
ExternalProject_Add(stub
GIT_REPOSITORY https://github.com/coolxv/cpp-stub.git
GIT_TAG 5e903b8e
GIT_SUBMODULES "src"
SOURCE_DIR "${TD_CONTRIB_DIR}/cpp-stub"
BINARY_DIR "${TD_CONTRIB_DIR}/cpp-stub/src"
......
cmake/taosadapter_CMakeLists.txt.in
浏览文件 @ d093b0e2
......@@ -2,7 +2,7 @@
# taosadapter
ExternalProject_Add(taosadapter
GIT_REPOSITORY https://github.com/taosdata/taosadapter.git
GIT_TAG 565ca21
GIT_TAG main
SOURCE_DIR "${TD_SOURCE_DIR}/tools/taosadapter"
BINARY_DIR ""
#BUILD_IN_SOURCE TRUE
......
cmake/taostools_CMakeLists.txt.in
浏览文件 @ d093b0e2
......@@ -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 "${TD_SOURCE_DIR}/tools/taos-tools"
BINARY_DIR ""
#BUILD_IN_SOURCE TRUE
......
contrib/CMakeLists.txt
浏览文件 @ d093b0e2
......@@ -77,11 +77,23 @@ if(${BUILD_WITH_LEVELDB})
cat("${TD_SUPPORT_DIR}/leveldb_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
endif(${BUILD_WITH_LEVELDB})
# rocksdb
if(${BUILD_WITH_ROCKSDB})
cat("${TD_SUPPORT_DIR}/rocksdb_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
add_definitions(-DUSE_ROCKSDB)
endif(${BUILD_WITH_ROCKSDB})
if (${BUILD_CONTRIB})
if(${BUILD_WITH_ROCKSDB})
cat("${TD_SUPPORT_DIR}/rocksdb_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
add_definitions(-DUSE_ROCKSDB)
endif()
else()
if (NOT ${TD_LINUX})
if(${BUILD_WITH_ROCKSDB})
cat("${TD_SUPPORT_DIR}/rocksdb_CMakeLists.txt.in" ${CONTRIB_TMP_FILE})
add_definitions(-DUSE_ROCKSDB)
endif(${BUILD_WITH_ROCKSDB})
else()
if(${BUILD_WITH_ROCKSDB})
add_definitions(-DUSE_ROCKSDB)
endif(${BUILD_WITH_ROCKSDB})
endif()
endif()
# canonical-raft
if(${BUILD_WITH_CRAFT})
......@@ -134,6 +146,11 @@ if(${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 "${CMAKE_GENERATOR}" .
......@@ -170,8 +187,8 @@ if(${BUILD_TEST})
PUBLIC $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/cpp-stub/src_darwin>
)
endif(${TD_DARWIN})
endif(${BUILD_TEST})
# cJson
......@@ -222,19 +239,113 @@ endif(${BUILD_WITH_LEVELDB})
# rocksdb
# To support rocksdb build on ubuntu: sudo apt-get install libgflags-dev
if(${BUILD_WITH_ROCKSDB})
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-error=maybe-uninitialized")
option(WITH_TESTS "" OFF)
option(WITH_BENCHMARK_TOOLS "" OFF)
option(WITH_TOOLS "" OFF)
option(WITH_LIBURING "" OFF)
option(ROCKSDB_BUILD_SHARED "Build shared versions of the RocksDB libraries" OFF)
add_subdirectory(rocksdb EXCLUDE_FROM_ALL)
target_include_directories(
rocksdb
PUBLIC $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/rocksdb/include>
)
endif(${BUILD_WITH_ROCKSDB})
if (${BUILD_WITH_UV})
if(${TD_LINUX})
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS_REL}")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS_REL}")
IF ("${CMAKE_BUILD_TYPE}" STREQUAL "")
SET(CMAKE_BUILD_TYPE Release)
endif()
endif(${TD_LINUX})
endif (${BUILD_WITH_UV})
if (${BUILD_WITH_ROCKSDB})
if (${BUILD_CONTRIB})
if(${TD_LINUX})
SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS_REL} -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")
if ("${CMAKE_BUILD_TYPE}" STREQUAL "")
SET(CMAKE_BUILD_TYPE Release)
endif()
endif(${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")
option(WITH_JNI "" OFF)
option(WITH_MD_LIBRARY "build with MD" OFF)
set(SYSTEM_LIBS ${SYSTEM_LIBS} shlwapi.lib rpcrt4.lib)
endif(${TD_WINDOWS})
if(${TD_DARWIN})
option(HAVE_THREAD_LOCAL "" OFF)
option(WITH_IOSTATS_CONTEXT "" OFF)
option(WITH_PERF_CONTEXT "" OFF)
endif(${TD_DARWIN})
option(WITH_FALLOCATE "" OFF)
option(WITH_JEMALLOC "" OFF)
option(WITH_GFLAGS "" OFF)
option(PORTABLE "" ON)
option(WITH_LIBURING "" OFF)
option(FAIL_ON_WARNINGS OFF)
option(WITH_TESTS "" OFF)
option(WITH_BENCHMARK_TOOLS "" OFF)
option(WITH_TOOLS "" OFF)
option(WITH_LIBURING "" OFF)
option(ROCKSDB_BUILD_SHARED "Build shared versions of the RocksDB libraries" OFF)
add_subdirectory(rocksdb EXCLUDE_FROM_ALL)
target_include_directories(
rocksdb
PUBLIC $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/rocksdb/include>
)
else()
if (NOT ${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")
option(WITH_JNI "" OFF)
option(WITH_MD_LIBRARY "build with MD" OFF)
set(SYSTEM_LIBS ${SYSTEM_LIBS} shlwapi.lib rpcrt4.lib)
endif(${TD_WINDOWS})
if(${TD_DARWIN})
option(HAVE_THREAD_LOCAL "" OFF)
option(WITH_IOSTATS_CONTEXT "" OFF)
option(WITH_PERF_CONTEXT "" OFF)
endif(${TD_DARWIN})
option(WITH_FALLOCATE "" OFF)
option(WITH_JEMALLOC "" OFF)
option(WITH_GFLAGS "" OFF)
option(PORTABLE "" ON)
option(WITH_LIBURING "" OFF)
option(FAIL_ON_WARNINGS OFF)
option(WITH_TESTS "" OFF)
option(WITH_BENCHMARK_TOOLS "" OFF)
option(WITH_TOOLS "" OFF)
option(WITH_LIBURING "" OFF)
option(ROCKSDB_BUILD_SHARED "Build shared versions of the RocksDB libraries" OFF)
add_subdirectory(rocksdb EXCLUDE_FROM_ALL)
target_include_directories(
rocksdb
PUBLIC $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/rocksdb/include>
)
endif()
endif()
endif()
# lucene
# To support build on ubuntu: sudo apt-get install libboost-all-dev
......@@ -242,10 +353,10 @@ if(${BUILD_WITH_LUCENE})
option(ENABLE_TEST "Enable the tests" OFF)
add_subdirectory(lucene EXCLUDE_FROM_ALL)
target_include_directories(
lucene++
lucene++
PUBLIC $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/lucene/include>
)
)
endif(${BUILD_WITH_LUCENE})
# NuRaft
......@@ -305,7 +416,7 @@ if(${BUILD_MSVCREGEX})
target_include_directories(msvcregex
PRIVATE "msvcregex"
)
target_link_libraries(msvcregex
target_link_libraries(msvcregex
INTERFACE Shell32
)
SET_TARGET_PROPERTIES(msvcregex PROPERTIES OUTPUT_NAME msvcregex)
......@@ -365,8 +476,8 @@ if(${BUILD_WITH_BDB})
IMPORTED_LOCATION "${CMAKE_CURRENT_SOURCE_DIR}/bdb/libdb.a"
INTERFACE_INCLUDE_DIRECTORIES "${CMAKE_CURRENT_SOURCE_DIR}/bdb"
)
target_link_libraries(bdb
INTERFACE pthread
target_link_libraries(bdb
INTERFACE pthread
)
endif(${BUILD_WITH_BDB})
......@@ -378,12 +489,12 @@ if(${BUILD_WITH_SQLITE})
IMPORTED_LOCATION "${CMAKE_CURRENT_SOURCE_DIR}/sqlite/.libs/libsqlite3.a"
INTERFACE_INCLUDE_DIRECTORIES "${CMAKE_CURRENT_SOURCE_DIR}/sqlite"
)
target_link_libraries(sqlite
INTERFACE m
INTERFACE pthread
target_link_libraries(sqlite
INTERFACE m
INTERFACE pthread
)
if(NOT TD_WINDOWS)
target_link_libraries(sqlite
target_link_libraries(sqlite
INTERFACE dl
)
endif(NOT TD_WINDOWS)
......@@ -391,22 +502,22 @@ endif(${BUILD_WITH_SQLITE})
# addr2line
if(${BUILD_ADDR2LINE})
if(NOT ${TD_WINDOWS})
check_include_file( "sys/types.h" HAVE_SYS_TYPES_H)
check_include_file( "sys/stat.h" HAVE_SYS_STAT_H )
check_include_file( "inttypes.h" HAVE_INTTYPES_H )
check_include_file( "stddef.h" HAVE_STDDEF_H )
check_include_file( "stdlib.h" HAVE_STDLIB_H )
check_include_file( "string.h" HAVE_STRING_H )
check_include_file( "memory.h" HAVE_MEMORY_H )
check_include_file( "strings.h" HAVE_STRINGS_H )
if(NOT ${TD_WINDOWS})
check_include_file( "sys/types.h" HAVE_SYS_TYPES_H)
check_include_file( "sys/stat.h" HAVE_SYS_STAT_H )
check_include_file( "inttypes.h" HAVE_INTTYPES_H )
check_include_file( "stddef.h" HAVE_STDDEF_H )
check_include_file( "stdlib.h" HAVE_STDLIB_H )
check_include_file( "string.h" HAVE_STRING_H )
check_include_file( "memory.h" HAVE_MEMORY_H )
check_include_file( "strings.h" HAVE_STRINGS_H )
check_include_file( "stdint.h" HAVE_STDINT_H )
check_include_file( "unistd.h" HAVE_UNISTD_H )
check_include_file( "sgidefs.h" HAVE_SGIDEFS_H )
check_include_file( "stdafx.h" HAVE_STDAFX_H )
check_include_file( "elf.h" HAVE_ELF_H )
check_include_file( "libelf.h" HAVE_LIBELF_H )
check_include_file( "libelf/libelf.h" HAVE_LIBELF_LIBELF_H)
check_include_file( "elf.h" HAVE_ELF_H )
check_include_file( "libelf.h" HAVE_LIBELF_H )
check_include_file( "libelf/libelf.h" HAVE_LIBELF_LIBELF_H)
check_include_file( "alloca.h" HAVE_ALLOCA_H )
check_include_file( "elfaccess.h" HAVE_ELFACCESS_H)
check_include_file( "sys/elf_386.h" HAVE_SYS_ELF_386_H )
......@@ -414,7 +525,7 @@ if(${BUILD_ADDR2LINE})
check_include_file( "sys/elf_sparc.h" HAVE_SYS_ELF_SPARC_H)
check_include_file( "sys/ia64/elf.h" HAVE_SYS_IA64_ELF_H )
set(VERSION 0.3.1)
set(PACKAGE_VERSION "\"${VERSION}\"")
set(PACKAGE_VERSION "\"${VERSION}\"")
configure_file(libdwarf/cmake/config.h.cmake config.h)
file(GLOB_RECURSE LIBDWARF_SOURCES "libdwarf/src/lib/libdwarf/*.c")
add_library(libdwarf STATIC ${LIBDWARF_SOURCES})
......@@ -434,6 +545,23 @@ if(${BUILD_ADDR2LINE})
endif(NOT ${TD_WINDOWS})
endif(${BUILD_ADDR2LINE})
# geos
if(${BUILD_GEOS})
if(${TD_LINUX})
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS_REL}")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS_REL}")
IF ("${CMAKE_BUILD_TYPE}" STREQUAL "")
SET(CMAKE_BUILD_TYPE Release)
endif()
endif(${TD_LINUX})
option(BUILD_SHARED_LIBS "Build GEOS with shared libraries" OFF)
add_subdirectory(geos EXCLUDE_FROM_ALL)
unset(CMAKE_CXX_STANDARD CACHE) # undo libgeos's setting of global CMAKE_CXX_STANDARD
target_include_directories(
geos_c
PUBLIC $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/geos/include>
)
endif(${BUILD_GEOS})
# ================================================================================================
# Build test
......
contrib/test/rocksdb/CMakeLists.txt
浏览文件 @ d093b0e2
message("contrib test/rocksdb:" ${BUILD_DEPENDENCY_TESTS})
add_executable(rocksdbTest "")
target_sources(rocksdbTest
PRIVATE
"${CMAKE_CURRENT_SOURCE_DIR}/main.c"
)
target_link_libraries(rocksdbTest rocksdb)
\ No newline at end of file
target_link_libraries(rocksdbTest rocksdb)
contrib/test/rocksdb/main.c
浏览文件 @ d093b0e2
#include <assert.h>
#include <bits/stdint-uintn.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
......@@ -9,38 +10,307 @@
const char DBPath[] = "rocksdb_c_simple_example";
const char DBBackupPath[] = "/tmp/rocksdb_c_simple_example_backup";
static const int32_t endian_test_var = 1;
#define IS_LITTLE_ENDIAN() (*(uint8_t *)(&endian_test_var) != 0)
#define TD_RT_ENDIAN() (IS_LITTLE_ENDIAN() ? TD_LITTLE_ENDIAN : TD_BIG_ENDIAN)
#define POINTER_SHIFT(p, b) ((void *)((char *)(p) + (b)))
static void *taosDecodeFixedU64(const void *buf, uint64_t *value) {
if (IS_LITTLE_ENDIAN()) {
memcpy(value, buf, sizeof(*value));
} else {
((uint8_t *)value)[7] = ((uint8_t *)buf)[0];
((uint8_t *)value)[6] = ((uint8_t *)buf)[1];
((uint8_t *)value)[5] = ((uint8_t *)buf)[2];
((uint8_t *)value)[4] = ((uint8_t *)buf)[3];
((uint8_t *)value)[3] = ((uint8_t *)buf)[4];
((uint8_t *)value)[2] = ((uint8_t *)buf)[5];
((uint8_t *)value)[1] = ((uint8_t *)buf)[6];
((uint8_t *)value)[0] = ((uint8_t *)buf)[7];
}
return POINTER_SHIFT(buf, sizeof(*value));
}
// ---- Fixed U64
static int32_t taosEncodeFixedU64(void **buf, uint64_t value) {
if (buf != NULL) {
if (IS_LITTLE_ENDIAN()) {
memcpy(*buf, &value, sizeof(value));
} else {
((uint8_t *)(*buf))[0] = value & 0xff;
((uint8_t *)(*buf))[1] = (value >> 8) & 0xff;
((uint8_t *)(*buf))[2] = (value >> 16) & 0xff;
((uint8_t *)(*buf))[3] = (value >> 24) & 0xff;
((uint8_t *)(*buf))[4] = (value >> 32) & 0xff;
((uint8_t *)(*buf))[5] = (value >> 40) & 0xff;
((uint8_t *)(*buf))[6] = (value >> 48) & 0xff;
((uint8_t *)(*buf))[7] = (value >> 56) & 0xff;
}
*buf = POINTER_SHIFT(*buf, sizeof(value));
}
return (int32_t)sizeof(value);
}
typedef struct KV {
uint64_t k1;
uint64_t k2;
} KV;
int kvSerial(KV *kv, char *buf) {
int len = 0;
len += taosEncodeFixedU64((void **)&buf, kv->k1);
len += taosEncodeFixedU64((void **)&buf, kv->k2);
return len;
}
const char *kvDBName(void *name) { return "kvDBname"; }
int kvDBComp(void *state, const char *aBuf, size_t aLen, const char *bBuf, size_t bLen) {
KV w1, w2;
memset(&w1, 0, sizeof(w1));
memset(&w2, 0, sizeof(w2));
char *p1 = (char *)aBuf;
char *p2 = (char *)bBuf;
// p1 += 1;
// p2 += 1;
p1 = taosDecodeFixedU64(p1, &w1.k1);
p2 = taosDecodeFixedU64(p2, &w2.k1);
p1 = taosDecodeFixedU64(p1, &w1.k2);
p2 = taosDecodeFixedU64(p2, &w2.k2);
if (w1.k1 < w2.k1) {
return -1;
} else if (w1.k1 > w2.k1) {
return 1;
}
if (w1.k2 < w2.k2) {
return -1;
} else if (w1.k2 > w2.k2) {
return 1;
}
return 0;
}
int kvDeserial(KV *kv, char *buf) {
char *p1 = (char *)buf;
// p1 += 1;
p1 = taosDecodeFixedU64(p1, &kv->k1);
p1 = taosDecodeFixedU64(p1, &kv->k2);
return 0;
}
int main(int argc, char const *argv[]) {
rocksdb_t * db;
rocksdb_t *db;
rocksdb_backup_engine_t *be;
rocksdb_options_t * options = rocksdb_options_create();
rocksdb_options_set_create_if_missing(options, 1);
// open DB
char *err = NULL;
db = rocksdb_open(options, DBPath, &err);
char *err = NULL;
const char *path = "/tmp/db";
// Write
rocksdb_writeoptions_t *writeoptions = rocksdb_writeoptions_create();
rocksdb_put(db, writeoptions, "key", 3, "value", 5, &err);
rocksdb_options_t *opt = rocksdb_options_create();
rocksdb_options_set_create_if_missing(opt, 1);
rocksdb_options_set_create_missing_column_families(opt, 1);
// Read
rocksdb_readoptions_t *readoptions = rocksdb_readoptions_create();
rocksdb_readoptions_set_snapshot(readoptions, rocksdb_create_snapshot(db));
// rocksdb_readoptions_set_snapshot(readoptions, rocksdb_create_snapshot(db));
int len = 1;
char buf[256] = {0};
size_t vallen = 0;
char * val = rocksdb_get(db, readoptions, "key", 3, &vallen, &err);
printf("val:%s\n", val);
char *val = rocksdb_get(db, readoptions, "key", 3, &vallen, &err);
snprintf(buf, vallen + 5, "val:%s", val);
printf("%ld %ld %s\n", strlen(val), vallen, buf);
char **cfName = calloc(len, sizeof(char *));
for (int i = 0; i < len; i++) {
cfName[i] = "test";
}
const rocksdb_options_t **cfOpt = malloc(len * sizeof(rocksdb_options_t *));
for (int i = 0; i < len; i++) {
cfOpt[i] = rocksdb_options_create_copy(opt);
if (i != 0) {
rocksdb_comparator_t *comp = rocksdb_comparator_create(NULL, NULL, kvDBComp, kvDBName);
rocksdb_options_set_comparator((rocksdb_options_t *)cfOpt[i], comp);
}
}
rocksdb_column_family_handle_t **cfHandle = malloc(len * sizeof(rocksdb_column_family_handle_t *));
db = rocksdb_open_column_families(opt, path, len, (const char *const *)cfName, cfOpt, cfHandle, &err);
{
rocksdb_readoptions_t *rOpt = rocksdb_readoptions_create();
size_t vlen = 0;
char *v = rocksdb_get_cf(db, rOpt, cfHandle[0], "key", strlen("key"), &vlen, &err);
printf("Get value %s, and len = %d\n", v, (int)vlen);
}
rocksdb_writeoptions_t *wOpt = rocksdb_writeoptions_create();
rocksdb_writebatch_t *wBatch = rocksdb_writebatch_create();
rocksdb_writebatch_put_cf(wBatch, cfHandle[0], "key", strlen("key"), "value", strlen("value"));
rocksdb_write(db, wOpt, wBatch, &err);
// Update
// rocksdb_put(db, writeoptions, "key", 3, "eulav", 5, &err);
rocksdb_readoptions_t *rOpt = rocksdb_readoptions_create();
size_t vlen = 0;
// Delete
rocksdb_delete(db, writeoptions, "key", 3, &err);
{
rocksdb_writeoptions_t *wOpt = rocksdb_writeoptions_create();
rocksdb_writebatch_t *wBatch = rocksdb_writebatch_create();
for (int i = 0; i < 100; i++) {
char buf[128] = {0};
KV kv = {.k1 = (100 - i) % 26, .k2 = i % 26};
kvSerial(&kv, buf);
rocksdb_writebatch_put_cf(wBatch, cfHandle[1], buf, sizeof(kv), "value", strlen("value"));
}
rocksdb_write(db, wOpt, wBatch, &err);
}
{
{
char buf[128] = {0};
KV kv = {.k1 = 0, .k2 = 0};
kvSerial(&kv, buf);
char *v = rocksdb_get_cf(db, rOpt, cfHandle[1], buf, sizeof(kv), &vlen, &err);
printf("Get value %s, and len = %d, xxxx\n", v, (int)vlen);
rocksdb_iterator_t *iter = rocksdb_create_iterator_cf(db, rOpt, cfHandle[1]);
rocksdb_iter_seek_to_first(iter);
int i = 0;
while (rocksdb_iter_valid(iter)) {
size_t klen, vlen;
const char *key = rocksdb_iter_key(iter, &klen);
const char *value = rocksdb_iter_value(iter, &vlen);
KV kv;
kvDeserial(&kv, (char *)key);
printf("kv1: %d\t kv2: %d, len:%d, value = %s\n", (int)(kv.k1), (int)(kv.k2), (int)(klen), value);
i++;
rocksdb_iter_next(iter);
}
rocksdb_iter_destroy(iter);
}
{
char buf[128] = {0};
KV kv = {.k1 = 0, .k2 = 0};
int len = kvSerial(&kv, buf);
rocksdb_iterator_t *iter = rocksdb_create_iterator_cf(db, rOpt, cfHandle[1]);
rocksdb_iter_seek(iter, buf, len);
if (!rocksdb_iter_valid(iter)) {
printf("invalid iter");
}
{
char buf[128] = {0};
KV kv = {.k1 = 100, .k2 = 0};
int len = kvSerial(&kv, buf);
// Read again
val = rocksdb_get(db, readoptions, "key", 3, &vallen, &err);
printf("val:%s\n", val);
rocksdb_iterator_t *iter = rocksdb_create_iterator_cf(db, rOpt, cfHandle[1]);
rocksdb_iter_seek(iter, buf, len);
if (!rocksdb_iter_valid(iter)) {
printf("invalid iter\n");
rocksdb_iter_seek_for_prev(iter, buf, len);
if (!rocksdb_iter_valid(iter)) {
printf("stay invalid iter\n");
} else {
size_t klen = 0, vlen = 0;
const char *key = rocksdb_iter_key(iter, &klen);
const char *value = rocksdb_iter_value(iter, &vlen);
KV kv;
kvDeserial(&kv, (char *)key);
printf("kv1: %d\t kv2: %d, len:%d, value = %s\n", (int)(kv.k1), (int)(kv.k2), (int)(klen), value);
}
}
}
}
}
// char *v = rocksdb_get_cf(db, rOpt, cfHandle[0], "key", strlen("key"), &vlen, &err);
// printf("Get value %s, and len = %d\n", v, (int)vlen);
rocksdb_column_family_handle_destroy(cfHandle[0]);
rocksdb_column_family_handle_destroy(cfHandle[1]);
rocksdb_close(db);
// {
// // rocksdb_options_t *Options = rocksdb_options_create();
// db = rocksdb_open(comm, path, &err);
// if (db != NULL) {
// rocksdb_options_t *cfo = rocksdb_options_create_copy(comm);
// rocksdb_comparator_t *cmp1 = rocksdb_comparator_create(NULL, NULL, kvDBComp, kvDBName);
// rocksdb_options_set_comparator(cfo, cmp1);
// rocksdb_column_family_handle_t *handle = rocksdb_create_column_family(db, cfo, "cf1", &err);
// rocksdb_column_family_handle_destroy(handle);
// rocksdb_close(db);
// db = NULL;
// }
// }
// int ncf = 2;
// rocksdb_column_family_handle_t **pHandle = malloc(ncf * sizeof(rocksdb_column_family_handle_t *));
// {
// rocksdb_options_t *options = rocksdb_options_create_copy(comm);
// rocksdb_comparator_t *cmp1 = rocksdb_comparator_create(NULL, NULL, kvDBComp, kvDBName);
// rocksdb_options_t *dbOpts1 = rocksdb_options_create_copy(comm);
// rocksdb_options_t *dbOpts2 = rocksdb_options_create_copy(comm);
// rocksdb_options_set_comparator(dbOpts2, cmp1);
// // rocksdb_column_family_handle_t *cf = rocksdb_create_column_family(db, dbOpts1, "cmp1", &err);
// const char *pName[] = {"default", "cf1"};
// const rocksdb_options_t **pOpts = malloc(ncf * sizeof(rocksdb_options_t *));
// pOpts[0] = dbOpts1;
// pOpts[1] = dbOpts2;
// rocksdb_options_t *allOptions = rocksdb_options_create_copy(comm);
// db = rocksdb_open_column_families(allOptions, "test", ncf, pName, pOpts, pHandle, &err);
// }
// // rocksdb_options_t *options = rocksdb_options_create();
// // rocksdb_options_set_create_if_missing(options, 1);
// // //rocksdb_open_column_families(const rocksdb_options_t *options, const char *name, int num_column_families,
// // const char *const *column_family_names,
// // const rocksdb_options_t *const *column_family_options,
// // rocksdb_column_family_handle_t **column_family_handles, char **errptr);
// for (int i = 0; i < 100; i++) {
// char buf[128] = {0};
// rocksdb_writeoptions_t *wopt = rocksdb_writeoptions_create();
// KV kv = {.k1 = i, .k2 = i};
// kvSerial(&kv, buf);
// rocksdb_put_cf(db, wopt, pHandle[0], buf, strlen(buf), (const char *)&i, sizeof(i), &err);
// }
// rocksdb_close(db);
// Write
// rocksdb_writeoptions_t *writeoptions = rocksdb_writeoptions_create();
// rocksdb_put(db, writeoptions, "key", 3, "value", 5, &err);
//// Read
// rocksdb_readoptions_t *readoptions = rocksdb_readoptions_create();
// rocksdb_readoptions_set_snapshot(readoptions, rocksdb_create_snapshot(db));
// size_t vallen = 0;
// char *val = rocksdb_get(db, readoptions, "key", 3, &vallen, &err);
// printf("val:%s\n", val);
//// Update
//// rocksdb_put(db, writeoptions, "key", 3, "eulav", 5, &err);
//// Delete
// rocksdb_delete(db, writeoptions, "key", 3, &err);
//// Read again
// val = rocksdb_get(db, readoptions, "key", 3, &vallen, &err);
// printf("val:%s\n", val);
// rocksdb_close(db);
return 0;
}
\ No newline at end of file
}
deps/arm/rocksdb_static/rocksdb/c.h 0 → 100644
浏览文件 @ d093b0e2
此差异已折叠。
deps/mips/rocksdb_static/rocksdb/c.h 0 → 100644
浏览文件 @ d093b0e2
此差异已折叠。
deps/x86/rocksdb_static/rocksdb/c.h 0 → 100644
浏览文件 @ d093b0e2
此差异已折叠。
docs/doxgen/CMakeLists.txt
浏览文件 @ d093b0e2
......@@ -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/01-index.md
浏览文件 @ d093b0e2
......@@ -5,7 +5,7 @@ description: This website contains the user manuals for TDengine, an open-source
slug: /
---
TDengine is an [open-source](https://tdengine.com/tdengine/open-source-time-series-database/), [cloud-native](https://tdengine.com/tdengine/cloud-native-time-series-database/) [time-series database](https://tdengine.com/tsdb/) optimized for the Internet of Things (IoT), Connected Cars, and Industrial IoT. It enables efficient, real-time data ingestion, processing, and monitoring of TB and even PB scale data per day, generated by billions of sensors and data collectors. This document is the TDengine user manual. It introduces the basic, as well as novel concepts, in TDengine, and also talks in detail about installation, features, SQL, APIs, operation, maintenance, kernel design, and other topics. It’s written mainly for architects, developers, and system administrators.
TDengine is an [open-source](https://tdengine.com/tdengine/open-source-time-series-database/), [cloud-native](https://tdengine.com/tdengine/cloud-native-time-series-database/) [time-series database](https://tdengine.com/tsdb/) optimized for the Internet of Things (IoT), Connected Cars, and Industrial IoT. It enables efficient, real-time data ingestion, processing, and monitoring of TB and even PB scale data per day, generated by billions of sensors and data collectors. This document is the TDengine user manual. It introduces the basic, as well as novel concepts, in TDengine, and also talks in detail about installation, features, SQL, APIs, operation, maintenance, kernel design, and other topics. It's written mainly for architects, developers, and system administrators.
To get an overview of TDengine, such as a feature list, benchmarks, and competitive advantages, please browse through the [Introduction](./intro) section.
......
docs/en/02-intro/index.md
浏览文件 @ d093b0e2
......@@ -44,7 +44,7 @@ For more details on features, please read through the entire documentation.
## Competitive Advantages
By making full use of [characteristics of time series data](https://tdengine.com/tsdb/characteristics-of-time-series-data/), TDengine differentiates itself from other [time series databases](https://tdengine.com/tsdb), with the following advantages.
By making full use of [characteristics of time series data](https://tdengine.com/tsdb/characteristics-of-time-series-data/), TDengine differentiates itself from other [time series databases](https://tdengine.com/tsdb/), with the following advantages.
- **[High-Performance](https://tdengine.com/tdengine/high-performance-time-series-database/)**: TDengine is the only time-series database to solve the high cardinality issue to support billions of data collection points while out performing other time-series databases for data ingestion, querying and data compression.
......@@ -57,7 +57,7 @@ By making full use of [characteristics of time series data](https://tdengine.com
- **[Easy Data Analytics](https://tdengine.com/tdengine/time-series-data-analytics-made-easy/)**: Through super tables, storage and compute separation, data partitioning by time interval, pre-computation and other means, TDengine makes it easy to explore, format, and get access to data in a highly efficient way.
- **[Open Source](https://tdengine.com/tdengine/open-source-time-series-database/)**: TDengine’s core modules, including cluster feature, are all available under open source licenses. It has gathered over 19k stars on GitHub. There is an active developer community, and over 140k running instances worldwide.
- **[Open Source](https://tdengine.com/tdengine/open-source-time-series-database/)**: TDengine's core modules, including cluster feature, are all available under open source licenses. It has gathered over 19k stars on GitHub. There is an active developer community, and over 140k running instances worldwide.
With TDengine, the total cost of ownership of your time-series data platform can be greatly reduced.
......@@ -109,8 +109,8 @@ As a high-performance, scalable and SQL supported time-series database, TDengine
| **System Performance Requirements** | **Not Applicable** | **Might Be Applicable** | **Very Applicable** | **Description** |
| ------------------------------------------------- | ------------------ | ----------------------- | ------------------- | --------------------------------------------------------------------------------------------------------------------------- |
| Very large total processing capacity | | | √ | TDengine’s cluster functions can easily improve processing capacity via multi-server coordination. |
| Extremely high-speed data processing | | | √ | TDengine’s storage and data processing are optimized for IoT, and can process data many times faster than similar products. |
| Very large total processing capacity | | | √ | TDengine's cluster functions can easily improve processing capacity via multi-server coordination. |
| Extremely high-speed data processing | | | √ | TDengine's storage and data processing are optimized for IoT, and can process data many times faster than similar products. |
| Extremely fast processing of high resolution data | | | √ | TDengine has achieved the same or better performance than other relational and NoSQL data processing systems. |
### System Maintenance Requirements
......@@ -123,13 +123,12 @@ As a high-performance, scalable and SQL supported time-series database, TDengine
## Comparison with other databases
- [Writing Performance Comparison of TDengine and InfluxDB ](https://tdengine.com/performance-comparison-of-tdengine-and-influxdb/)
- [Query Performance Comparison of TDengine and InfluxDB](https://tdengine.com/query-performance-comparison-test-report-tdengine-vs-influxdb/)
- [TDengine vs OpenTSDB](https://tdengine.com/performance-tdengine-vs-opentsdb/)
- [TDengine vs Cassandra](https://tdengine.com/performance-tdengine-vs-cassandra/)
- [TDengine vs InfluxDB](https://tdengine.com/performance-tdengine-vs-influxdb/)
- [TDengine vs. InfluxDB](https://tdengine.com/tsdb-comparison-influxdb-vs-tdengine/)
- [TDengine vs. TimescaleDB](https://tdengine.com/tsdb-comparison-timescaledb-vs-tdengine/)
- [TDengine vs. OpenTSDB](https://tdengine.com/performance-tdengine-vs-opentsdb/)
- [TDengine vs. Cassandra](https://tdengine.com/performance-tdengine-vs-cassandra/)
## More readings
- [Introduction to Time-Series Database](https://tdengine.com/tsdb/)
- [Introduction to TDengine competitive advantages](https://tdengine.com/tdengine/)
docs/en/04-concept/index.md
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......@@ -127,7 +127,7 @@ To make full use of time-series data characteristics, TDengine adopts a strategy
If the metric data of multiple DCPs are traditionally written into a single table, due to uncontrollable network delays, the timing of the data from different DCPs arriving at the server cannot be guaranteed, write operations must be protected by locks, and metric data from one DCP cannot be guaranteed to be continuously stored together. **One table for one data collection point can ensure the best performance of insert and query of a single data collection point to the greatest possible extent.**
TDengine suggests using DCP ID as the table name (like d1001 in the above table). Each DCP may collect one or multiple metrics (like the `current`, `voltage`, `phase` as above). Each metric has a corresponding column in the table. The data type for a column can be int, float, string and others. In addition, the first column in the table must be a timestamp. TDengine uses the timestamp as the index, and won’t build the index on any metrics stored. Column wise storage is used.
TDengine suggests using DCP ID as the table name (like d1001 in the above table). Each DCP may collect one or multiple metrics (like the `current`, `voltage`, `phase` as above). Each metric has a corresponding column in the table. The data type for a column can be int, float, string and others. In addition, the first column in the table must be a timestamp. TDengine uses the timestamp as the index, and won't build the index on any metrics stored. Column wise storage is used.
Complex devices, such as connected cars, may have multiple DCPs. In this case, multiple tables are created for a single device, one table per DCP.
......
docs/en/05-get-started/01-docker.md
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......@@ -6,7 +6,7 @@ description: This document describes how to install TDengine in a Docker contain
This document describes how to install TDengine in a Docker container and perform queries and inserts.
- The easiest way to explore TDengine is through [TDengine Cloud](http://cloud.tdengine.com).
- The easiest way to explore TDengine is through [TDengine Cloud](https://cloud.tdengine.com).
- To get started with TDengine in a non-containerized environment, see [Quick Install from Package](../../get-started/package).
- If you want to view the source code, build TDengine yourself, or contribute to the project, see the [TDengine GitHub repository](https://github.com/taosdata/TDengine).
......
docs/en/05-get-started/03-package.md
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......@@ -10,7 +10,7 @@ import PkgListV3 from "/components/PkgListV3";
This document describes how to install TDengine on Linux/Windows/macOS and perform queries and inserts.
- The easiest way to explore TDengine is through [TDengine Cloud](http://cloud.tdengine.com).
- The easiest way to explore TDengine is through [TDengine Cloud](https://cloud.tdengine.com).
- To get started with TDengine on Docker, see [Quick Install on Docker](../../get-started/docker).
- If you want to view the source code, build TDengine yourself, or contribute to the project, see the [TDengine GitHub repository](https://github.com/taosdata/TDengine).
......@@ -20,6 +20,19 @@ The standard server installation package includes `taos`, `taosd`, `taosAdapter`
The TDengine Community Edition is released as Deb and RPM packages. The Deb package can be installed on Debian, Ubuntu, and derivative systems. The RPM package can be installed on CentOS, RHEL, SUSE, and derivative systems. A .tar.gz package is also provided for enterprise customers, and you can install TDengine over `apt-get` as well. The .tar.tz package includes `taosdump` and the TDinsight installation script. If you want to use these utilities with the Deb or RPM package, download and install taosTools separately. TDengine can also be installed on x64 Windows and x64/m1 macOS.
## Operating environment requirements
In the Linux system, the minimum requirements for the operating environment are as follows:
linux core version - 3.10.0-1160.83.1.el7.x86_64;
glibc version - 2.17;
If compiling and installing through clone source code, it is also necessary to meet the following requirements:
cmake version - 3.26.4 or above;
gcc version - 9.3.1 or above;
## Installation
<Tabs>
......@@ -102,7 +115,7 @@ sudo apt-get install tdengine
:::tip
This installation method is supported only for Debian and Ubuntu.
::::
:::
</TabItem>
<TabItem label="Windows" value="windows">
......@@ -208,6 +221,8 @@ The following `launchctl` commands can help you manage TDengine service:
- Check TDengine Server status: `sudo launchctl list | grep taosd`
- Check TDengine Server status details: `launchctl print system/com.tdengine.taosd`
:::info
- Please use `sudo` to run `launchctl` to manage _com.tdengine.taosd_ with administrator privileges.
- The administrator privilege is required for service management to enhance security.
......
docs/en/07-develop/01-connect/_connect_java.mdx
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......@@ -12,4 +12,4 @@ When using REST connection, the feature of bulk pulling can be enabled if the si
{{#include docs/examples/java/src/main/java/com/taos/example/WSConnectExample.java:main}}
```
More configuration about connection，please refer to [Java Connector](/reference/connector/java)
More configuration about connection, please refer to [Java Connector](/reference/connector/java)
docs/en/07-develop/01-connect/_connect_php.mdx
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```php title="原生连接"
```php title=""native"
{{#include docs/examples/php/connect.php}}
```
docs/en/07-develop/01-connect/index.md
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......@@ -33,7 +33,7 @@ There are two ways for a connector to establish connections to TDengine:
For REST and native connections, connectors provide similar APIs for performing operations and running SQL statements on your databases. The main difference is the method of establishing the connection, which is not visible to users.
Key differences：
Key differences:
3. The REST connection is more accessible with cross-platform support, however it results in a 30% performance downgrade.
1. The TDengine client driver (taosc) has the highest performance with all the features of TDengine like [Parameter Binding](/reference/connector/cpp#parameter-binding-api), [Subscription](/reference/connector/cpp#subscription-and-consumption-api), etc.
......@@ -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>
```
......@@ -198,7 +198,7 @@ The sample code below are based on dotnet6.0, they may need to be adjusted if yo
<TabItem label="R" value="r">
1. Download [taos-jdbcdriver-version-dist.jar](https://repo1.maven.org/maven2/com/taosdata/jdbc/taos-jdbcdriver/3.0.0/).
2. Install the dependency package `RJDBC`：
2. Install the dependency package `RJDBC`:
```R
install.packages("RJDBC")
......@@ -213,7 +213,7 @@ If the client driver (taosc) is already installed, then the C connector is alrea
</TabItem>
<TabItem label="PHP" value="php">
**Download Source Code Package and Unzip：**
**Download Source Code Package and Unzip: **
```shell
curl -L -o php-tdengine.tar.gz https://github.com/Yurunsoft/php-tdengine/archive/refs/tags/v1.0.2.tar.gz \
......@@ -223,13 +223,13 @@ curl -L -o php-tdengine.tar.gz https://github.com/Yurunsoft/php-tdengine/archive
> Version number `v1.0.2` is only for example, it can be replaced to any newer version, please check available version from [TDengine PHP Connector Releases](https://github.com/Yurunsoft/php-tdengine/releases).
**Non-Swoole Environment：**
**Non-Swoole Environment: **
```shell
phpize && ./configure && make -j && make install
```
**Specify TDengine Location：**
**Specify TDengine Location: **
```shell
phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/3.0.0.0 && make -j && make install
......@@ -238,7 +238,7 @@ phpize && ./configure --with-tdengine-dir=/usr/local/Cellar/tdengine/3.0.0.0 &&
> `--with-tdengine-dir=` is followed by the TDengine installation location.
> This way is useful in case TDengine location can't be found automatically or macOS.
**Swoole Environment：**
**Swoole Environment: **
```shell
phpize && ./configure --enable-swoole && make -j && make install
......@@ -288,6 +288,6 @@ Prior to establishing connection, please make sure TDengine is already running a
</Tabs>
:::tip
If the connection fails, in most cases it's caused by improper configuration for FQDN or firewall. Please refer to the section "Unable to establish connection" in [FAQ](https://docs.tdengine.com/train-faq/faq).
If the connection fails, in most cases it's caused by improper configuration for FQDN or firewall. Please refer to the section "Unable to establish connection" in [FAQ](../../train-faq/faq).
:::
docs/en/07-develop/03-insert-data/01-sql-writing.mdx
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......@@ -33,7 +33,7 @@ The below SQL statement is used to insert one row into table "d1001".
INSERT INTO d1001 VALUES (ts1, 10.3, 219, 0.31);
```
`ts1` is Unix timestamp, the timestamps which is larger than the difference between current time and KEEP in config is only allowed. For further detial, refer to [TDengine SQL insert timestamp section](/taos-sql/insert).
`ts1` is Unix timestamp, the timestamps which is larger than the difference between current time and KEEP in config is only allowed. For further detail, refer to [TDengine SQL insert timestamp section](/taos-sql/insert).
### Insert Multiple Rows
......@@ -43,7 +43,7 @@ Multiple rows can be inserted in a single SQL statement. The example below inser
INSERT INTO d1001 VALUES (ts2, 10.2, 220, 0.23) (ts2, 10.3, 218, 0.25);
```
`ts1` and `ts2` is Unix timestamp, the timestamps which is larger than the difference between current time and KEEP in config is only allowed. For further detial, refer to [TDengine SQL insert timestamp section](/taos-sql/insert).
`ts1` and `ts2` is Unix timestamp, the timestamps which is larger than the difference between current time and KEEP in config is only allowed. For further detail, refer to [TDengine SQL insert timestamp section](/taos-sql/insert).
### Insert into Multiple Tables
......@@ -53,7 +53,7 @@ Data can be inserted into multiple tables in the same SQL statement. The example
INSERT INTO d1001 VALUES (ts1, 10.3, 219, 0.31) (ts2, 12.6, 218, 0.33) d1002 VALUES (ts3, 12.3, 221, 0.31);
```
`ts1`, `ts2` and `ts3` is Unix timestamp, the timestamps which is larger than the difference between current time and KEEP in config is only allowed. For further detial, refer to [TDengine SQL insert timestamp section](/taos-sql/insert).
`ts1`, `ts2` and `ts3` is Unix timestamp, the timestamps which is larger than the difference between current time and KEEP in config is only allowed. For further detail, refer to [TDengine SQL insert timestamp section](/taos-sql/insert).
For more details about `INSERT` please refer to [INSERT](/taos-sql/insert).
......
docs/en/07-develop/03-insert-data/30-influxdb-line.mdx
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......@@ -69,7 +69,7 @@ For more details please refer to [InfluxDB Line Protocol](https://docs.influxdat
## Query Examples
If you want query the data of `location=California.LosAngeles,groupid=2`，here is the query SQL:
If you want query the data of `location=California.LosAngeles,groupid=2`, here is the query SQL:
```sql
SELECT * FROM meters WHERE location = "California.LosAngeles" AND groupid = 2;
......
docs/en/07-develop/03-insert-data/40-opentsdb-telnet.mdx
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......@@ -84,7 +84,7 @@ Query OK, 4 row(s) in set (0.005399s)
## Query Examples
If you want query the data of `location=California.LosAngeles groupid=3`，here is the query SQL:
If you want query the data of `location=California.LosAngeles groupid=3`, here is the query SQL:
```sql
SELECT * FROM `meters.current` WHERE location = "California.LosAngeles" AND groupid = 3;
......
docs/en/07-develop/03-insert-data/50-opentsdb-json.mdx
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......@@ -97,7 +97,7 @@ Query OK, 2 row(s) in set (0.004076s)
## Query Examples
If you want query the data of "tags": {"location": "California.LosAngeles", "groupid": 1}，here is the query SQL:
If you want query the data of "tags": {"location": "California.LosAngeles", "groupid": 1}, here is the query SQL:
```sql
SELECT * FROM `meters.current` WHERE location = "California.LosAngeles" AND groupid = 3;
......
docs/en/07-develop/03-insert-data/60-high-volume.md
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......@@ -49,7 +49,7 @@ If the data source is Kafka, then the application program is a consumer of Kafka
On the server side, database configuration parameter `vgroups` needs to be set carefully to maximize the system performance. If it's set too low, the system capability can't be utilized fully; if it's set too big, unnecessary resource competition may be produced. A normal recommendation for `vgroups` parameter is 2 times of the number of CPU cores. However, depending on the actual system resources, it may still need to tuned.
For more configuration parameters, please refer to [Database Configuration](../../../taos-sql/database) and [Server Configuration](../../../reference/config)。
For more configuration parameters, please refer to [Database Configuration](../../../taos-sql/database) and [Server Configuration](../../../reference/config).
## Sample Programs
......@@ -98,7 +98,7 @@ The main Program is responsible for:
3. Start reading threads
4. Output writing speed every 10 seconds
The main program provides 4 parameters for tuning：
The main program provides 4 parameters for tuning:
1. The number of reading threads, default value is 1
2. The number of writing threads, default value is 2
......@@ -192,7 +192,7 @@ TDENGINE_JDBC_URL="jdbc:TAOS://localhost:6030?user=root&password=taosdata"
If you want to launch the sample program on a remote server, please follow below steps:
1. Package the sample programs. Execute below command under directory `TDengine/docs/examples/java` ：
1. Package the sample programs. Execute below command under directory `TDengine/docs/examples/java`:
```
mvn package
```
......@@ -385,7 +385,7 @@ SQLWriter class encapsulates the logic of composing SQL and writing data. Please
pip3 install faster-fifo
```
3. Click the "Copy" in the above sample programs to copy `fast_write_example.py` 、 `sql_writer.py` and `mockdatasource.py`.
3. Click the "Copy" in the above sample programs to copy `fast_write_example.py`, `sql_writer.py`, and `mockdatasource.py`.
4. Execute the program
......
docs/en/07-develop/03-insert-data/_py_kafka.mdx
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### python Kafka 客户端
### python Kafka client
For python kafka client, please refer to [kafka client](https://cwiki.apache.org/confluence/display/KAFKA/Clients#Clients-Python). In this document, we use [kafka-python](http://github.com/dpkp/kafka-python).
......@@ -88,7 +88,7 @@ In addition to python's built-in multithreading and multiprocessing library, we
<details>
<summary>kafka_example_consumer</summary>
`kafka_example_consumer` is `consumer`，which is responsible for consuming data from kafka and writing it to TDengine.
`kafka_example_consumer` is `consumer`, which is responsible for consuming data from kafka and writing it to TDengine.
```py
{{#include docs/examples/python/kafka_example_consumer.py}}
......
docs/en/07-develop/03-insert-data/_rust_schemaless.mdx 0 → 100644
浏览文件 @ d093b0e2
```rust
{{#include docs/examples/rust/nativeexample/examples/schemaless_insert_line.rs}}
```
docs/en/07-develop/04-query-data/index.mdx
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......@@ -20,10 +20,10 @@ import CAsync from "./_c_async.mdx";
## Introduction
SQL is used by TDengine as its query language. Application programs can send SQL statements to TDengine through REST API or connectors. TDengine's CLI `taos` can also be used to execute ad hoc SQL queries. Here is the list of major query functionalities supported by TDengine：
SQL is used by TDengine as its query language. Application programs can send SQL statements to TDengine through REST API or connectors. TDengine's CLI `taos` can also be used to execute ad hoc SQL queries. Here is the list of major query functionalities supported by TDengine:
- Query on single column or multiple columns
- Filter on tags or data columns：>, <, =, <\>, like
- Filter on tags or data columns: >, <, =, <\>, like
- Grouping of results: `Group By` - Sorting of results: `Order By` - Limit the number of results: `Limit/Offset`
- Windowed aggregate queries for time windows (interval), session windows (session), and state windows (state_window)
- Arithmetic on columns of numeric types or aggregate results
......@@ -160,7 +160,7 @@ In the section describing [Insert](/develop/insert-data/sql-writing), a database
:::note
1. With either REST connection or native connection, the above sample code works well.
2. Please note that `use db` can't be used in case of REST connection because it's stateless.
2. Please note that `use db` can't be used in case of REST connection because it's stateless. You can specify the database name by either the REST endpoint's parameter or <db_name>.<table_name> in the SQL command.
:::
......
docs/en/07-develop/07-tmq.mdx
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......@@ -23,7 +23,7 @@ By subscribing to a topic, a consumer can obtain the latest data in that topic i
To implement these features, TDengine indexes its write-ahead log (WAL) file for fast random access and provides configurable methods for replacing and retaining this file. You can define a retention period and size for this file. For information, see the CREATE DATABASE statement. In this way, the WAL file is transformed into a persistent storage engine that remembers the order in which events occur. However, note that configuring an overly long retention period for your WAL files makes database compression inefficient. TDengine then uses the WAL file instead of the time-series database as its storage engine for queries in the form of topics. TDengine reads the data from the WAL file; uses a unified query engine instance to perform filtering, transformations, and other operations; and finally pushes the data to consumers.
Tips:The default data subscription is to consume data from the wal. If the wal is deleted, the consumed data will be incomplete. At this time, you can set the parameter experimental.snapshot.enable to true to obtain all data from the tsdb, but in this way, the consumption order of the data cannot be guaranteed. Therefore, it is recommended to set a reasonable retention policy for WAL based on your consumption situation to ensure that you can subscribe all data from WAL.
Tips: Data subscription is to consume data from the wal. If some wal files are deleted according to WAL retention policy, the deleted data can't be consumed any more. So you need to set a reasonable value for parameter `WAL_RETENTION_PERIOD` or `WAL_RETENTION_SIZE` when creating the database and make sure your application consume the data in a timely way to make sure there is no data loss. This behavior is similar to Kafka and other widely used message queue products.
## Data Schema and API
......@@ -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
......@@ -222,7 +228,7 @@ A database including one supertable and two subtables is created as follows:
```sql
DROP DATABASE IF EXISTS tmqdb;
CREATE DATABASE tmqdb;
CREATE DATABASE tmqdb WAL_RETENTION_PERIOD 3600;
CREATE TABLE tmqdb.stb (ts TIMESTAMP, c1 INT, c2 FLOAT, c3 VARCHAR(16)) TAGS(t1 INT, t3 VARCHAR(16));
CREATE TABLE tmqdb.ctb0 USING tmqdb.stb TAGS(0, "subtable0");
CREATE TABLE tmqdb.ctb1 USING tmqdb.stb TAGS(1, "subtable1");
......@@ -238,6 +244,8 @@ The following SQL statement creates a topic in TDengine:
CREATE TOPIC topic_name AS SELECT ts, c1, c2, c3 FROM tmqdb.stb WHERE c1 > 1;
```
- There is an upper limit to the number of topics created, controlled by the parameter tmqMaxTopicNum, with a default of 20
Multiple subscription types are supported.
#### Subscribe to a Column
......@@ -259,14 +267,15 @@ You can subscribe to a topic through a SELECT statement. Statements that specify
Syntax:
```sql
CREATE TOPIC topic_name AS STABLE stb_name
CREATE TOPIC topic_name [with meta] AS STABLE stb_name [where_condition]
```
Creating a topic in this manner differs from a `SELECT * from stbName` statement as follows:
- The table schema can be modified.
- Unstructured data is returned. The format of the data returned changes based on the supertable schema.
- A different table schema may exist for every data block to be processed.
- The 'with meta' parameter is optional. When selected, statements such as creating super tables and sub tables will be returned, mainly used for Taosx to perform super table migration
- The 'where_condition' parameter is optional and will be used to filter and subscribe to sub tables that meet the criteria. Where conditions cannot have ordinary columns, only tags or tbnames. Functions can be used in where conditions to filter tags, but cannot be aggregate functions because sub table tag values cannot be aggregated. It can also be a constant expression, such as 2>1 (subscribing to all child tables), Or false (subscribe to 0 sub tables)
- The data returned does not include tags.
### Subscribe to a Database
......@@ -274,10 +283,12 @@ Creating a topic in this manner differs from a `SELECT * from stbName` statement
Syntax:
```sql
CREATE TOPIC topic_name [WITH META] AS DATABASE db_name;
CREATE TOPIC topic_name [with meta] AS DATABASE db_name;
```
This SQL statement creates a subscription to all tables in the database. You can add the `WITH META` parameter to include schema changes in the subscription, including creating and deleting supertables; adding, deleting, and modifying columns; and creating, deleting, and modifying the tags of subtables. Consumers can determine the message type from the API. Note that this differs from Kafka.
This SQL statement creates a subscription to all tables in the database.
- The 'with meta' parameter is optional. When selected, it will return statements for creating all super tables and sub tables in the database, mainly used for Taosx database migration
## Create a Consumer
......@@ -285,16 +296,15 @@ You configure the following parameters when creating a consumer:
| Parameter | Type | Description | Remarks |
| :----------------------------: | :-----: | -------------------------------------------------------- | ------------------------------------------- |
| `td.connect.ip` | string | Used in establishing a connection; same as `taos_connect` | Only valid for establishing native connection |
| `td.connect.user` | string | Used in establishing a connection; same as `taos_connect` | Only valid for establishing native connection |
| `td.connect.pass` | string | Used in establishing a connection; same as `taos_connect` | Only valid for establishing native connection |
| `td.connect.port` | string | Used in establishing a connection; same as `taos_connect` | Only valid for establishing native connection |
| `group.id` | string | Consumer group ID; consumers with the same ID are in the same group | **Required**. Maximum length: 192. |
| `td.connect.ip` | string | IP address of the server side | |
| `td.connect.user` | string | User Name | |
| `td.connect.pass` | string | Password | |
| `td.connect.port` | string | Port of the server side | |
| `group.id` | string | Consumer group ID; consumers with the same ID are in the same group | **Required**. Maximum length: 192. Each topic can create up to 100 consumer groups. |
| `client.id` | string | Client ID | Maximum length: 192. |
| `auto.offset.reset` | enum | Initial offset for the consumer group | Specify `earliest`, `latest`, or `none`(default) |
| `enable.auto.commit` | boolean | Commit automatically; true: user application doesn't need to explicitly commit; false: user application need to handle commit by itself | Default value is true |
| `auto.commit.interval.ms` | integer | Interval for automatic commits, in milliseconds |
| `experimental.snapshot.enable` | boolean | Specify whether to consume data in TSDB; true: both data in WAL and in TSDB can be consumed; false: only data in WAL can be consumed | default value: false |
| `msg.with.table.name` | boolean | Specify whether to deserialize table names from messages | default value: false
The method of specifying these parameters depends on the language used:
......@@ -312,7 +322,6 @@ tmq_conf_set(conf, "group.id", "cgrpName");
tmq_conf_set(conf, "td.connect.user", "root");
tmq_conf_set(conf, "td.connect.pass", "taosdata");
tmq_conf_set(conf, "auto.offset.reset", "earliest");
tmq_conf_set(conf, "experimental.snapshot.enable", "true");
tmq_conf_set(conf, "msg.with.table.name", "true");
tmq_conf_set_auto_commit_cb(conf, tmq_commit_cb_print, NULL);
......@@ -327,6 +336,7 @@ Java programs use the following parameters:
| Parameter | Type | Description | Remarks |
| ----------------------------- | ------ | ----------------------------------------------------------------------------------------------------------------------------- |
| `td.connect.type` | string | connection type: "jni" means native connection, "ws" means websocket connection, the default is "jni" |
| `bootstrap.servers` | string |Connection address, such as `localhost:6030` |
| `value.deserializer` | string | Value deserializer; to use this method, implement the `com.taosdata.jdbc.tmq.Deserializer` interface or inherit the `com.taosdata.jdbc.tmq.ReferenceDeserializer` type |
| `value.deserializer.encoding` | string | Specify the encoding for string deserialization | |
......@@ -368,7 +378,6 @@ conf := &tmq.ConfigMap{
"td.connect.port": "6030",
"client.id": "test_tmq_c",
"enable.auto.commit": "false",
"experimental.snapshot.enable": "true",
"msg.with.table.name": "true",
}
consumer, err := NewConsumer(conf)
......@@ -402,23 +411,6 @@ from taos.tmq import Consumer
consumer = Consumer({"group.id": "local", "td.connect.ip": "127.0.0.1"})
```
Python programs use the following parameters:
| Parameter | Type | Description | Remarks |
|:---------:|:----:|:-----------:|:-------:|
| `td.connect.ip` | string | Used in establishing a connection||
| `td.connect.user` | string | Used in establishing a connection||
| `td.connect.pass` | string | Used in establishing a connection||
| `td.connect.port` | string | Used in establishing a connection||
| `group.id` | string | Consumer group ID; consumers with the same ID are in the same group | **Required**. Maximum length: 192 |
| `client.id` | string | Client ID | Maximum length: 192 |
| `msg.with.table.name` | string | Specify whether to deserialize table names from messages | pecify `true` or `false` |
| `enable.auto.commit` | string | Commit automatically | pecify `true` or `false` |
| `auto.commit.interval.ms` | string | Interval for automatic commits, in milliseconds | |
| `auto.offset.reset` | string | Initial offset for the consumer group | Specify `earliest`, `latest`, or `none`(default) |
| `experimental.snapshot.enable` | string | Specify whether it's allowed to consume messages from the WAL or from TSDB | Specify `true` or `false` |
| `enable.heartbeat.background` | string | Backend heartbeat; if enabled, the consumer does not go offline even if it has not polled for a long time | Specify `true` or `false` |
</TabItem>
<TabItem label="Node.JS" value="Node.JS">
......
docs/en/07-develop/08-cache.md
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......@@ -10,10 +10,10 @@ TDengine uses various kinds of caching techniques to efficiently write and query
TDengine uses an insert-driven cache management policy, known as first in, first out (FIFO). This policy differs from read-driven "least recently used (LRU)" cache management. A FIFO policy stores the latest data in cache and flushes the oldest data from cache to disk when the cache usage reaches a threshold. In IoT use cases, the most recent data or the current state is most important. The cache policy in TDengine, like much of the design and architecture of TDengine, is based on the nature of IoT data.
When you create a database, you can configure the size of the write cache on each vnode. The **vgroups** parameter determines the number of vgroups that process data in the database, and the **buffer** parameter determines the size of the write cache for each vnode.
When you create a database, you can configure the size of the write cache on each vnode. The **vgroups** parameter determines the number of vgroups that process data in the database, and the **buffer** parameter determines the size of the write cache for each vnode. The unit of buffer is MB.
```sql
create database db0 vgroups 100 buffer 16MB
create database db0 vgroups 100 buffer 16
```
In theory, larger cache sizes are always better. However, at a certain point, it becomes impossible to improve performance by increasing cache size. In most scenarios, you can retain the default cache settings.
......@@ -28,10 +28,10 @@ When you create a database, you can configure whether the latest data from every
## Metadata Cache
To improve query and write performance, each vnode caches the metadata that it receives. When you create a database, you can configure the size of the metadata cache through the *pages* and *pagesize* parameters.
To improve query and write performance, each vnode caches the metadata that it receives. When you create a database, you can configure the size of the metadata cache through the *pages* and *pagesize* parameters. The unit of pagesize is kb.
```sql
create database db0 pages 128 pagesize 16kb
create database db0 pages 128 pagesize 16
```
The preceding SQL statement creates 128 pages on each vnode in the `db0` database. Each page has a 16 KB metadata cache.
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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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此差异已折叠。
docs/en/12-taos-sql/02-database.md
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......@@ -72,8 +72,8 @@ database_option: {
- 0: The database can contain multiple supertables.
- 1: The database can contain only one supertable.
- STT_TRIGGER: specifies the number of file merges triggered by flushed files. The default is 8, ranging from 1 to 16. For high-frequency scenarios with few tables, it is recommended to use the default configuration or a smaller value for this parameter; For multi-table low-frequency scenarios, it is recommended to configure this parameter with a larger value.
- TABLE_PREFIX：The prefix length in the table name that is ignored when distributing table to vnode based on table name.
- TABLE_SUFFIX：The suffix length in the table name that is ignored when distributing table to vnode based on table name.
- TABLE_PREFIX: The prefix in the table name that is ignored when distributing a table to a vgroup when it's a positive number, or only the prefix is used when distributing a table to a vgroup, the default value is 0; For example, if the table name v30001, then "0001" is used if TSDB_PREFIX is set to 2 but "v3" is used if TSDB_PREFIX is set to -2; It can help you to control the distribution of tables.
- TABLE_SUFFIX: The suffix in the table name that is ignored when distributing a table to a vgroup when it's a positive number, or only the suffix is used when distributing a table to a vgroup, the default value is 0; For example, if the table name v30001, then "v300" is used if TSDB_SUFFIX is set to 2 but "01" is used if TSDB_SUFFIX is set to -2; It can help you to control the distribution of tables.
- TSDB_PAGESIZE: The page size of the data storage engine in a vnode. The unit is KB. The default is 4 KB. The range is 1 to 16384, that is, 1 KB to 16 MB.
- WAL_RETENTION_PERIOD: specifies the maximum time of which WAL files are to be kept for consumption. This parameter is used for data subscription. Enter a time in seconds. The default value 0. A value of 0 indicates that WAL files are not required to keep for consumption. Alter it with a proper value at first to create topics.
- WAL_RETENTION_SIZE: specifies the maximum total size of which WAL files are to be kept for consumption. This parameter is used for data subscription. Enter a size in KB. The default value is 0. A value of 0 indicates that the total size of WAL files to keep for consumption has no upper limit.
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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/04-stable.md
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......@@ -33,7 +33,7 @@ column_definition:
SHOW STABLES [LIKE tb_name_wildcard];
```
The preceding SQL statement shows all supertables in the current TDengine database, including the name, creation time, number of columns, number of tags, and number of subtables for each supertable.
The preceding SQL statement shows all supertables in the current TDengine database.
### View the CREATE Statement for a Supertable
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docs/en/12-taos-sql/05-insert.md
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......@@ -82,7 +82,7 @@ One or multiple rows can be inserted into multiple tables in a single SQL statem
```sql
INSERT INTO d1001 VALUES ('2021-07-13 14:06:34.630', 10.2, 219, 0.32) ('2021-07-13 14:06:35.779', 10.15, 217, 0.33)
d1002 (ts, current, phase) VALUES ('2021-07-13 14:06:34.255', 10.27, 0.31）;
d1002 (ts, current, phase) VALUES ('2021-07-13 14:06:34.255', 10.27, 0.31);
```
## Automatically Create Table When Inserting
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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] ...
......@@ -373,7 +373,7 @@ FROM temp_stable t1, temp_stable t2
WHERE t1.ts = t2.ts AND t1.deviceid = t2.deviceid AND t1.status=0;
```
For sub-table and super table：
For sub-table and super table:
```sql
SELECT *
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docs/en/12-taos-sql/07-tag-index.md
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......@@ -6,14 +6,14 @@ description: Use Tag Index to Improve Query Performance
## Introduction
Prior to TDengine 3.0.3.0 (excluded)，only one index is created by default on the first tag of each super talbe, but it's not allowed to dynamically create index on any other tags. From version 3.0.30, you can dynamically create index on any tag of any type. The index created automatically by TDengine is still valid. Query performance can benefit from indexes if you use properly.
Prior to TDengine 3.0.3.0 (excluded), only one index is created by default on the first tag of each super table, but it's not allowed to dynamically create index on any other tags. From version 3.0.30, you can dynamically create index on any tag of any type. The index created automatically by TDengine is still valid. Query performance can benefit from indexes if you use properly.
## Syntax
1. The syntax of creating an index
```sql
CREATE INDEX index_name ON tbl_name (tagColName）
CREATE INDEX index_name ON tbl_name (tagColName)
```
In the above statement, `index_name` if the name of the index, `tbl_name` is the name of the super table,`tagColName` is the name of the tag on which the index is being created. `tagColName` can be any type supported by TDengine.
......@@ -48,4 +48,4 @@ You can also add filter conditions to limit the results.
6. You can' create index on a normal table or a child table.
7. If the unique values of a tag column are too few, it's better not to create index on such tag columns, the benefit would be very small.
\ No newline at end of file
7. If the unique values of a tag column are too few, it's better not to create index on such tag columns, the benefit would be very small.
docs/en/12-taos-sql/10-function.md
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......@@ -5,9 +5,9 @@ description: This document describes the standard SQL functions available in TDe
toc_max_heading_level: 4
---
## Single Row Functions
## Scalar Functions
Single row functions return a result for each row.
Scalar functions return one result for each row.
### Mathematical Functions
......@@ -434,7 +434,7 @@ TO_ISO8601(expr [, timezone])
**More explanations**:
- You can specify a time zone in the following format: [z/Z, +/-hhmm, +/-hh, +/-hh:mm]。 For example, TO_ISO8601(1, "+00:00").
- You can specify a time zone in the following format: [z/Z, +/-hhmm, +/-hh, +/-hh:mm]. For example, TO_ISO8601(1, "+00:00").
- If the input is a UNIX timestamp, the precision of the returned value is determined by the digits of the input timestamp
- If the input is a column of TIMESTAMP type, the precision of the returned value is same as the precision set for the current data base in use
......@@ -459,12 +459,17 @@ TO_JSON(str_literal)
#### TO_UNIXTIMESTAMP
```sql
TO_UNIXTIMESTAMP(expr)
TO_UNIXTIMESTAMP(expr [, return_timestamp])
return_timestamp: {
0
| 1
}
```
**Description**: UNIX timestamp converted from a string of date/time format
**Return value type**: BIGINT
**Return value type**: BIGINT, TIMESTAMP
**Applicable column types**: VARCHAR and NCHAR
......@@ -476,6 +481,7 @@ TO_UNIXTIMESTAMP(expr)
- The input string must be compatible with ISO8601/RFC3339 standard, NULL will be returned if the string can't be converted
- The precision of the returned timestamp is same as the precision set for the current data base in use
- return_timestamp indicates whether the returned value type is TIMESTAMP or not. If this parameter set to 1, function will return TIMESTAMP type. Otherwise function will return BIGINT type. If parameter is omitted, default return value type is BIGINT.
### Time and Date Functions
......@@ -620,7 +626,7 @@ algo_type: {
**Applicable table types**: standard tables and supertables
**Explanations**：
**Explanations**:
- _p_ is in range [0,100], when _p_ is 0, the result is same as using function MIN; when _p_ is 100, the result is same as function MAX.
- `algo_type` can only be input as `default` or `t-digest` Enter `default` to use a histogram-based algorithm. Enter `t-digest` to use the t-digest algorithm to calculate the approximation of the quantile. `default` is used by default.
- The approximation result of `t-digest` algorithm is sensitive to input data order. For example, when querying STable with different input data order there might be minor differences in calculated results.
......@@ -666,7 +672,7 @@ If you input a specific column, the number of non-null values in the column is r
ELAPSED(ts_primary_key [, time_unit])
```
**Description**：`elapsed` function can be used to calculate the continuous time length in which there is valid data. If it's used with `INTERVAL` clause, the returned result is the calculated time length within each time window. If it's used without `INTERVAL` caluse, the returned result is the calculated time length within the specified time range. Please be noted that the return value of `elapsed` is the number of `time_unit` in the calculated time length.
**Description**: `elapsed` function can be used to calculate the continuous time length in which there is valid data. If it's used with `INTERVAL` clause, the returned result is the calculated time length within each time window. If it's used without `INTERVAL` clause, the returned result is the calculated time length within the specified time range. Please be noted that the return value of `elapsed` is the number of `time_unit` in the calculated time length.
**Return value type**: Double if the input value is not NULL;
......@@ -674,7 +680,7 @@ ELAPSED(ts_primary_key [, time_unit])
**Applicable tables**: table, STable, outer in nested query
**Explanations**：
**Explanations**:
- `ts_primary_key` parameter can only be the first column of a table, i.e. timestamp primary key.
- The minimum value of `time_unit` is the time precision of the database. If `time_unit` is not specified, the time precision of the database is used as the default time unit. Time unit specified by `time_unit` can be:
1b (nanoseconds), 1u (microseconds), 1a (milliseconds), 1s (seconds), 1m (minutes), 1h (hours), 1d (days), or 1w (weeks)
......@@ -752,7 +758,7 @@ SUM(expr)
HYPERLOGLOG(expr)
```
**Description**：
**Description**:
The cardinal number of a specific column is returned by using hyperloglog algorithm. The benefit of using hyperloglog algorithm is that the memory usage is under control when the data volume is huge.
However, when the data volume is very small, the result may be not accurate, it's recommended to use `select count(data) from (select unique(col) as data from table)` in this case.
......@@ -766,10 +772,10 @@ HYPERLOGLOG(expr)
### HISTOGRAM
```sql
HISTOGRAM(expr，bin_type, bin_description, normalized)
HISTOGRAM(expr, bin_type, bin_description, normalized)
```
**Description**：Returns count of data points in user-specified ranges.
**Description**: Returns count of data points in user-specified ranges.
**Return value type** If normalized is set to 1, a DOUBLE is returned; otherwise a BIGINT is returned
......@@ -777,18 +783,18 @@ HISTOGRAM(expr，bin_type, bin_description, normalized)
**Applicable table types**: table, STable
**Explanations**：
- bin_type: parameter to indicate the bucket type, valid inputs are: "user_input", "linear_bin", "log_bin"。
- bin_description: parameter to describe how to generate buckets，can be in the following JSON formats for each bin_type respectively:
**Explanations**:
- bin_type: parameter to indicate the bucket type, valid inputs are: "user_input", "linear_bin", "log_bin".
- bin_description: parameter to describe how to generate buckets can be in the following JSON formats for each bin_type respectively:
- "user_input": "[1, 3, 5, 7]":
User specified bin values.
- "linear_bin": "{"start": 0.0, "width": 5.0, "count": 5, "infinity": true}"
"start" - bin starting point. "width" - bin offset. "count" - number of bins generated. "infinity" - whether to add（-inf, inf）as start/end point in generated set of bins.
"start" - bin starting point. "width" - bin offset. "count" - number of bins generated. "infinity" - whether to add (-inf, inf) as start/end point in generated set of bins.
The above "linear_bin" descriptor generates a set of bins: [-inf, 0.0, 5.0, 10.0, 15.0, 20.0, +inf].
- "log_bin": "{"start":1.0, "factor": 2.0, "count": 5, "infinity": true}"
"start" - bin starting point. "factor" - exponential factor of bin offset. "count" - number of bins generated. "infinity" - whether to add（-inf, inf）as start/end point in generated range of bins.
"start" - bin starting point. "factor" - exponential factor of bin offset. "count" - number of bins generated. "infinity" - whether to add (-inf, inf) as start/end point in generated range of bins.
The above "linear_bin" descriptor generates a set of bins: [-inf, 1.0, 2.0, 4.0, 8.0, 16.0, +inf].
- normalized: setting to 1/0 to turn on/off result normalization. Valid values are 0 or 1.
......@@ -861,10 +867,16 @@ FIRST(expr)
### INTERP
```sql
INTERP(expr)
INTERP(expr [, ignore_null_values])
ignore_null_values: {
0
| 1
}
```
**Description**: The value that matches the specified timestamp range is returned, if existing; or an interpolation value is returned.
**Description**: The value that matches the specified timestamp range is returned, if existing; or an interpolation value is returned. The value of `ignore_null_values` can be 0 or 1, 1 means null values are ignored. The default value of this parameter is 0.
**Return value type**: Same as the column being operated upon
......@@ -877,10 +889,11 @@ INTERP(expr)
- `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).
- `INTERP` can only be used to interpolate in single timeline. So it must be used with `partition by tbname` when it's used on a STable.
- 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).
......@@ -890,7 +903,7 @@ INTERP(expr)
- 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
......@@ -986,19 +999,14 @@ SAMPLE(expr, k)
**Description**: _k_ sampling values of a specific column. The applicable range of _k_ is [1,1000].
**Return value type**: Same as the column being operated plus the associated timestamp
**Return value type**: Same as the column being operated
**Applicable data types**: Any data type except for tags of STable
**Applicable data types**: Any data type
**Applicable nested query**: Inner query and Outer query
**Applicable table types**: standard tables and supertables
**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
### TAIL
......@@ -1043,11 +1051,11 @@ TOP(expr, k)
UNIQUE(expr)
```
**Description**: The values that occur the first time in the specified column. The effect is similar to `distinct` keyword, but it can also be used to match tags or timestamp. The first occurrence of a timestamp or tag is used.
**Description**: The values that occur the first time in the specified column. The effect is similar to `distinct` keyword.
**Return value type**:Same as the data type of the column being operated upon
**Applicable column types**: Any data types except for timestamp
**Applicable column types**: Any data types
**Applicable table types**: table, STable
......@@ -1076,7 +1084,6 @@ 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
......@@ -1100,8 +1107,7 @@ 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。
- It can be used together with a selected column. For example: select \_rowts, DERIVATIVE() from.
### DIFF
......@@ -1125,7 +1131,7 @@ ignore_negative: {
**More explanation**:
- The number of result rows is the number of rows subtracted by one, no output for the first row
- It can be used together with a selected column. For example: select \_rowts, DIFF() from。
- It can be used together with a selected column. For example: select \_rowts, DIFF() from.
### IRATE
......@@ -1163,7 +1169,6 @@ 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
......@@ -1177,7 +1182,7 @@ STATECOUNT(expr, oper, val)
**Applicable parameter values**:
- oper : Can be one of `'LT'` (lower than), `'GT'` (greater than), `'LE'` (lower than or equal to), `'GE'` (greater than or equal to), `'NE'` (not equal to), `'EQ'` (equal to), the value is case insensitive, the value must be in quotes.
- val ： Numeric types
- val: Numeric types
**Return value type**: Integer
......@@ -1189,7 +1194,6 @@ 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
......@@ -1204,7 +1208,7 @@ STATEDURATION(expr, oper, val, unit)
**Applicable parameter values**:
- oper : Can be one of `'LT'` (lower than), `'GT'` (greater than), `'LE'` (lower than or equal to), `'GE'` (greater than or equal to), `'NE'` (not equal to), `'EQ'` (equal to), the value is case insensitive, the value must be in quotes.
- val ： Numeric types
- val: Numeric types
- unit: The unit of time interval. Enter one of the following options: 1b (nanoseconds), 1u (microseconds), 1a (milliseconds), 1s (seconds), 1m (minutes), 1h (hours), 1d (days), or 1w (weeks) If you do not enter a unit of time, the precision of the current database is used by default.
**Return value type**: Integer
......@@ -1217,7 +1221,6 @@ 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
......@@ -1235,7 +1238,6 @@ 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/12-distinguished.md
浏览文件 @ d093b0e2
......@@ -21,7 +21,7 @@ part_list can be any scalar expression, such as a column, constant, scalar funct
A PARTITION BY clause is processed as follows:
- The PARTITION BY clause must occur after the WHERE clause
- The PARTITION BY caluse partitions the data according to the specified dimensions, then perform computation on each partition. The performed computation is determined by the rest of the statement - a window clause, GROUP BY clause, or SELECT clause.
- The PARTITION BY clause partitions the data according to the specified dimensions, then perform computation on each partition. The performed computation is determined by the rest of the statement - a window clause, GROUP BY clause, or SELECT clause.
- The PARTITION BY clause can be used together with a window clause or GROUP BY clause. In this case, the window or GROUP BY clause takes effect on every partition. For example, the following statement partitions the table by the location tag, performs downsampling over a 10 minute window, and returns the maximum value:
```sql
......@@ -69,19 +69,20 @@ These pseudocolumns occur after the aggregation clause.
`FILL` clause is used to specify how to fill when there is data missing in any window, including:
1. NONE: No fill (the default fill mode)
2. VALUE：Fill with a fixed value, which should be specified together, for example `FILL(VALUE, 1.23)` Note: The value filled depends on the data type. For example, if you run FILL(VALUE 1.23) on an integer column, the value 1 is filled.
3. PREV：Fill with the previous non-NULL value, `FILL(PREV)`
4. NULL：Fill with NULL, `FILL(NULL)`
5. LINEAR：Fill with the closest non-NULL value, `FILL(LINEAR)`
6. NEXT：Fill with the next non-NULL value, `FILL(NEXT)`
2. VALUE: Fill with a fixed value, which should be specified together, for example `FILL(VALUE, 1.23)` Note: The value filled depends on the data type. For example, if you run FILL(VALUE 1.23) on an integer column, the value 1 is filled.
3. PREV: Fill with the previous non-NULL value, `FILL(PREV)`
4. NULL: Fill with NULL, `FILL(NULL)`
5. LINEAR: Fill with the closest non-NULL value, `FILL(LINEAR)`
6. NEXT: Fill with the next non-NULL value, `FILL(NEXT)`
In the above filling modes, except for `NONE` mode, the `fill` clause will be ignored if there is no data in the defined time range, i.e. no data would be filled and the query result would be empty. This behavior is reasonable when the filling mode is `PREV`, `NEXT`, `LINEAR`, because filling can't be performed if there is not any data. For filling modes `NULL` and `VALUE`, however, filling can be performed even though there is not any data, filling or not depends on the choice of user's application. To accomplish the need of this force filling behavior and not break the behavior of existing filling modes, TDengine added two new filling modes since version 3.0.3.0.
1. NULL_F: Fill `NULL` by force
2. VALUE_F: Fill `VALUE` by force
The detailed beaviors of `NULL`, `NULL_F`, `VALUE`, and VALUE_F are described below：
- When used with `INTERVAL`: `NULL_F` and `VALUE_F` are filling by force；`NULL` and `VALUE` don't fill by force. The behavior of each filling mode is exactly same as what the name suggests.
The detailed beaviors of `NULL`, `NULL_F`, `VALUE`, and VALUE_F are described below:
- When used with `INTERVAL`: `NULL_F` and `VALUE_F` are filling by force; `NULL` and `VALUE` don't fill by force. The behavior of each filling mode is exactly same as what the name suggests.
- When used with `INTERVAL` in stream processing: `NULL_F` and `NULL` are same, i.e. don't fill by force; `VALUE_F` and `VALUE` and same, i.e. don't fill by force. It's suggested that there is no filling by force in stream processing.
- When used with `INTERP`: `NULL` and `NULL_F` and same, i.e. filling by force; `VALUE` and `VALUE_F` are same, i.e. filling by force. It's suggested that there is always filling by force when used with `INTERP`.
......@@ -97,7 +98,7 @@ The detailed beaviors of `NULL`, `NULL_F`, `VALUE`, and VALUE_F are described be
There are two kinds of time windows: sliding window and flip time/tumbling window.
The `INTERVAL` clause is used to generate time windows of the same time interval. The `SLIDING` parameter is used to specify the time step for which the time window moves forward. The query is performed on one time window each time, and the time window moves forward with time. When defining a continuous query, both the size of the time window and the step of forward sliding time need to be specified. As shown in the figure blow, [t0s, t0e] ，[t1s , t1e]， [t2s, t2e] are respectively the time ranges of three time windows on which continuous queries are executed. The time step for which time window moves forward is marked by `sliding time`. Query, filter and aggregate operations are executed on each time window respectively. When the time step specified by `SLIDING` is same as the time interval specified by `INTERVAL`, the sliding time window is actually a flip time/tumbling window.
The `INTERVAL` clause is used to generate time windows of the same time interval. The `SLIDING` parameter is used to specify the time step for which the time window moves forward. The query is performed on one time window each time, and the time window moves forward with time. When defining a continuous query, both the size of the time window and the step of forward sliding time need to be specified. As shown in the figure blow, [t0s, t0e], [t1s, t1e], [t2s, t2e] are respectively the time ranges of three time windows on which continuous queries are executed. The time step for which time window moves forward is marked by `sliding time`. Query, filter and aggregate operations are executed on each time window respectively. When the time step specified by `SLIDING` is same as the time interval specified by `INTERVAL`, the sliding time window is actually a flip time/tumbling window.
![TDengine Database Time Window](./timewindow-1.webp)
......@@ -121,7 +122,7 @@ Please note that the `timezone` parameter should be configured to be the same va
### State Window
In case of using integer, bool, or string to represent the status of a device at any given moment, continuous rows with the same status belong to a status window. Once the status changes, the status window closes. As shown in the following figure, there are two state windows according to status, [2019-04-28 14:22:07，2019-04-28 14:22:10] and [2019-04-28 14:22:11，2019-04-28 14:22:12].
In case of using integer, bool, or string to represent the status of a device at any given moment, continuous rows with the same status belong to a status window. Once the status changes, the status window closes. As shown in the following figure, there are two state windows according to status, [2019-04-28 14:22:07, 2019-04-28 14:22:10] and [2019-04-28 14:22:11, 2019-04-28 14:22:12].
![TDengine Database Status Window](./timewindow-3.webp)
......@@ -145,7 +146,7 @@ SELECT tbname, _wstart, CASE WHEN voltage >= 205 and voltage <= 235 THEN 1 ELSE
### Session Window
The primary key, i.e. timestamp, is used to determine which session window a row belongs to. As shown in the figure below, if the limit of time interval for the session window is specified as 12 seconds, then the 6 rows in the figure constitutes 2 time windows, [2019-04-28 14:22:10，2019-04-28 14:22:30] and [2019-04-28 14:23:10，2019-04-28 14:23:30] because the time difference between 2019-04-28 14:22:30 and 2019-04-28 14:23:10 is 40 seconds, which exceeds the time interval limit of 12 seconds.
The primary key, i.e. timestamp, is used to determine which session window a row belongs to. As shown in the figure below, if the limit of time interval for the session window is specified as 12 seconds, then the 6 rows in the figure constitutes 2 time windows, [2019-04-28 14:22:10, 2019-04-28 14:22:30] and [2019-04-28 14:23:10, 2019-04-28 14:23:30] because the time difference between 2019-04-28 14:22:30 and 2019-04-28 14:23:10 is 40 seconds, which exceeds the time interval limit of 12 seconds.
![TDengine Database Session Window](./timewindow-2.webp)
......@@ -178,7 +179,7 @@ select _wstart, _wend, count(*) from t event_window start with c1 > 0 end with c
### Examples
A table of intelligent meters can be created by the SQL statement below：
A table of intelligent meters can be created by the SQL statement below:
```
CREATE TABLE meters (ts TIMESTAMP, current FLOAT, voltage INT, phase FLOAT) TAGS (location BINARY(64), groupId INT);
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```sql
CREATE STREAM [IF NOT EXISTS] stream_name [stream_options] INTO stb_name SUBTABLE(expression) AS subquery
stream_options: {
TRIGGER [AT_ONCE | WINDOW_CLOSE | MAX_DELAY time]
WATERMARK time
TRIGGER [AT_ONCE | WINDOW_CLOSE | MAX_DELAY time]
WATERMARK time
IGNORE EXPIRED [0|1]
DELETE_MARK time
FILL_HISTORY [0|1]
}
```
......@@ -109,7 +112,7 @@ SHOW STREAMS;
When you create a stream, you can use the TRIGGER parameter to specify triggering conditions for it.
For non-windowed processing, triggering occurs in real time. For windowed processing, there are three methods of triggering，the default value is AT_ONCE:
For non-windowed processing, triggering occurs in real time. For windowed processing, there are three methods of triggering, the default value is AT_ONCE:
1. AT_ONCE: triggers on write
......@@ -141,3 +144,27 @@ The data in expired windows is tagged as expired. TDengine stream processing pro
2. Recalculate the data. In this method, all data in the window is reobtained from the database and recalculated. The latest results are then returned.
In both of these methods, configuring the watermark is essential for obtaining accurate results (if expired data is dropped) and avoiding repeated triggers that affect system performance (if expired data is recalculated).
## Supported functions
All [scalar functions](../function/#scalar-functions) are available in stream processing. All [Aggregate functions](../function/#aggregate-functions) and [Selection functions](../function/#selection-functions) are available in stream processing, except the followings:
- [leastsquares](../function/#leastsquares)
- [percentile](../function/#percentile)
- [top](../function/#top)
- [bottom](../function/#bottom)
- [elapsed](../function/#elapsed)
- [interp](../function/#interp)
- [derivative](../function/#derivative)
- [irate](../function/#irate)
- [twa](../function/#twa)
- [histogram](../function/#histogram)
- [diff](../function/#diff)
- [statecount](../function/#statecount)
- [stateduration](../function/#stateduration)
- [csum](../function/#csum)
- [mavg](../function/#mavg)
- [sample](../function/#sample)
- [tail](../function/#tail)
- [unique](../function/#unique)
- [mode](../function/#mode)
docs/en/12-taos-sql/17-json.md
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- The maximum length of keys in JSON is 256 bytes, and key must be printable ASCII characters. The maximum total length of a JSON is 4,096 bytes.
- JSON format：
- JSON format:
- The input string for JSON can be empty, i.e. "", "\t", or NULL, but it can't be non-NULL string, bool or array.
- object can be {}, and the entire JSON is empty if so. Key can be "", and it's ignored if so.
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1. If there are escape characters in identifiers (database name, table name, column name)
- Identifier without ``: Error will be returned because identifier must be constituted of digits, ASCII characters or underscore and can't be started with digits
- Identifier quoted with ``： Original content is kept, no escaping
- Identifier quoted with ``: Original content is kept, no escaping
2. If there are escape characters in values
- The escape characters will be escaped as the above table. If the escape character doesn't match any supported one, the escape character "\" will be ignored.
- "%" and "\_" are used as wildcards in `like`. `\%` and `\_` should be used to represent literal "%" and "\_" in `like`,. If `\%` and `\_` are used out of `like` context, the evaluation result is "`\%`"and "`\_`", instead of "%" and "\_".
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- 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
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......@@ -81,7 +81,7 @@ Provides information about user-created databases. Similar to SHOW DATABASES.
| 3 | ntables | INT | Number of standard tables and subtables (not including supertables) |
| 4 | vgroups | INT | Number of vgroups. It should be noted that `vnodes` is a TDengine keyword and needs to be escaped with ` when used as a column name. |
| 6 | replica | INT | Number of replicas. It should be noted that `replica` is a TDengine keyword and needs to be escaped with ` when used as a column name. |
| 7 | strict | BINARY(3) | Strong consistency. It should be noted that `strict` is a TDengine keyword and needs to be escaped with ` when used as a column name. |
| 7 | strict | BINARY(4) | Obsoleted |
| 8 | duration | INT | Duration for storage of single files. It should be noted that `duration` is a TDengine keyword and needs to be escaped with ` when used as a column name. |
| 9 | keep | INT | Data retention period. It should be noted that `keep` is a TDengine keyword and needs to be escaped with ` when used as a column name. |
| 10 | buffer | INT | Write cache size per vnode, in MB. It should be noted that `buffer` is a TDengine keyword and needs to be escaped with ` when used as a column name. |
......@@ -120,6 +120,9 @@ Provides information about user-defined functions.
| 5 | create_time | TIMESTAMP | Creation time |
| 6 | code_len | INT | Length of the source code |
| 7 | bufsize | INT | Buffer size |
| 8 | func_language | BINARY(31) | UDF programming language |
| 9 | func_body | BINARY(16384) | UDF function body |
| 10 | func_version | INT | UDF function version. starting from 0. Increasing by 1 each time it is updated|
## INS_INDEXES
......@@ -181,7 +184,7 @@ Provides information about standard tables and subtables.
## INS_COLUMNS
| # | **列名** | **数据类型** | **说明** |
| # | **Column** | **Data Type** | **Description** |
| --- | :---------: | ------------- | ---------------------- |
| 1 | table_name | BINARY(192) | Table name |
| 2 | db_name | BINARY(64) | Database name |
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| 1 | consumer_id | BIGINT | Consumer ID |
| 2 | consumer_group | BINARY(192) | Consumer group |
| 3 | client_id | BINARY(192) | Client ID (user-defined) |
| 4 | status | BINARY(20) | Consumer status |
| 4 | status | BINARY(20) | Consumer status. All possible status include: ready(consumer is in normal state), lost(the connection between consumer and mnode is broken), rebalance(the redistribution of vgroups that belongs to current consumer is now in progress), unknown(consumer is in invalid state)
| 5 | topics | BINARY(204) | Subscribed topic. Returns one row for each topic. |
| 6 | up_time | TIMESTAMP | Time of first connection to TDengine Server |
| 7 | subscribe_time | TIMESTAMP | Time of first subscription |
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description: This document describes how to use the SHOW statement in TDengine.
---
`SHOW` command can be used to get brief system information. To get details about metadata, information, and status in the system, please use `select` to query the tables in database `INFORMATION_SCHEMA`.
`SHOW` command can be used to get brief system information. To get details about metadata, information, and status in the system, please use `select` to query the tables in database `INFORMATION_SCHEMA`.
## SHOW APPS
......@@ -36,7 +36,7 @@ Shows information about connections to the system.
SHOW CONSUMERS;
```
Shows information about all active consumers in the system.
Shows information about all consumers in the system.
## SHOW CREATE DATABASE
......@@ -129,6 +129,14 @@ SHOW QNODES;
Shows information about qnodes in the system.
## SHOW QUERIES
```sql
SHOW QUERIES;
```
Shows the queries in progress in the system.
## SHOW SCORES
```sql
......@@ -179,10 +187,10 @@ SHOW TABLE DISTRIBUTED table_name;
Shows how table data is distributed.
Examples： Below is an example of this command to display the block distribution of table `d0` in detailed format.
Examples: Below is an example of this command to display the block distribution of table `d0` in detailed format.
```sql
show table distributed d0\G;
show table distributed d0\G;
```
<details>
......@@ -193,31 +201,31 @@ _block_dist: Total_Blocks=[5] Total_Size=[93.65 KB] Average_size=[18.73 KB] Comp
Total_Blocks : Table `d0` contains total 5 blocks
Total_Size: The total size of all the data blocks in table `d0` is 93.65 KB
Total_Size: The total size of all the data blocks in table `d0` is 93.65 KB
Average_size: The average size of each block is 18.73 KB
Compression_Ratio: The data compression rate is 23.98%
*************************** 2.row ***************************
_block_dist: Total_Rows=[20000] Inmem_Rows=[0] MinRows=[3616] MaxRows=[4096] Average_Rows=[4000]
Total_Rows: Table `d0` contains 20,000 rows
Inmem_Rows： The rows still in memory, i.e. not committed in disk, is 0, i.e. none such rows
Inmem_Rows: The rows still in memory, i.e. not committed in disk, is 0, i.e. none such rows
MinRows： The minimum number of rows in a block is 3,616
MinRows: The minimum number of rows in a block is 3,616
MaxRows： The maximum number of rows in a block is 4,096B
MaxRows: The maximum number of rows in a block is 4,096B
Average_Rows： The average number of rows in a block is 4,000
Average_Rows: The average number of rows in a block is 4,000
*************************** 3.row ***************************
_block_dist: Total_Tables=[1] Total_Files=[2]
Total_Tables: The number of child tables, 1 in this example
Total_Tables: The number of child tables, 1 in this example
Total_Files： The number of files storing the table's data, 2 in this example
Total_Files: The number of files storing the table's data, 2 in this example
*************************** 4.row ***************************
......@@ -353,7 +361,7 @@ SHOW VARIABLES;
SHOW DNODE dnode_id VARIABLES;
```
Shows the working configuration of the parameters that must be the same on each node. You can also specify a dnode to show the working configuration for that node.
Shows the working configuration of the parameters that must be the same on each node. You can also specify a dnode to show the working configuration for that node.
## SHOW VGROUPS
......@@ -361,7 +369,7 @@ Shows the working configuration of the parameters that must be the same on each
SHOW [db_name.]VGROUPS;
```
Shows information about all vgroups in the current database.
Shows information about all vgroups in the current database.
## SHOW VNODES
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| - | :------- | :-------- | :------- |
| 1 | ALTER ACCOUNT | Deprecated| This Enterprise Edition-only statement has been removed. It returns the error "This statement is no longer supported."
| 2 | ALTER ALL DNODES | Added | Modifies the configuration of all dnodes.
| 3 | ALTER DATABASE | Modified | Deprecated<ul><li>QUORUM: Specified the required number of confirmations. TDengine 3.0 provides strict consistency by default and doesn't allow to change to weak consitency. </li><li>BLOCKS: Specified the memory blocks used by each vnode. BUFFER is now used to specify the size of the write cache pool for each vnode. </li><li>UPDATE: Specified whether update operations were supported. All databases now support updating data in certain columns. </li><li>CACHELAST: Specified how to cache the newest row of data. CACHEMODEL now replaces CACHELAST. </li><li>COMP: Cannot be modified. <br/>Added</li><li>CACHEMODEL: Specifies whether to cache the latest subtable data. </li><li>CACHESIZE: Specifies the size of the cache for the newest subtable data. </li><li>WAL_FSYNC_PERIOD: Replaces the FSYNC parameter. </li><li>WAL_LEVEL: Replaces the WAL parameter. </li><li>WAL_RETENTION_PERIOD: specifies the time after which WAL files are deleted. This parameter is used for data subscription. </li><li>WAL_RETENTION_SIZE: specifies the size at which WAL files are deleted. This parameter is used for data subscription. <br/>Modified</li><li>REPLICA: Cannot be modified. </li><li>KEEP: Now supports units. </li></ul>
| 3 | ALTER DATABASE | Modified | Deprecated<ul><li>QUORUM: Specified the required number of confirmations. TDengine 3.0 provides strict consistency by default and doesn't allow to change to weak consistency. </li><li>BLOCKS: Specified the memory blocks used by each vnode. BUFFER is now used to specify the size of the write cache pool for each vnode. </li><li>UPDATE: Specified whether update operations were supported. All databases now support updating data in certain columns. </li><li>CACHELAST: Specified how to cache the newest row of data. CACHEMODEL now replaces CACHELAST. </li><li>COMP: Cannot be modified. <br/>Added</li><li>CACHEMODEL: Specifies whether to cache the latest subtable data. </li><li>CACHESIZE: Specifies the size of the cache for the newest subtable data. </li><li>WAL_FSYNC_PERIOD: Replaces the FSYNC parameter. </li><li>WAL_LEVEL: Replaces the WAL parameter. </li><li>WAL_RETENTION_PERIOD: specifies the time after which WAL files are deleted. This parameter is used for data subscription. </li><li>WAL_RETENTION_SIZE: specifies the size at which WAL files are deleted. This parameter is used for data subscription. <br/>Modified</li><li>REPLICA: Cannot be modified. </li><li>KEEP: Now supports units. </li></ul>
| 4 | ALTER STABLE | Modified | Deprecated<ul><li>CHANGE TAG: Modified the name of a tag. Replaced by RENAME TAG. <br/>Added</li><li>RENAME TAG: Replaces CHANGE TAG. </li><li>COMMENT: Specifies comments for a supertable. </li></ul>
| 5 | ALTER TABLE | Modified | Deprecated<ul><li>CHANGE TAG: Modified the name of a tag. Replaced by RENAME TAG. <br/>Added</li><li>RENAME TAG: Replaces CHANGE TAG. </li><li>COMMENT: Specifies comments for a standard table. </li><li>TTL: Specifies the time-to-live for a standard table. </li></ul>
| 6 | ALTER USER | Modified | Deprecated<ul><li>PRIVILEGE: Specified user permissions. Replaced by GRANT and REVOKE. <br/>Added</li><li>ENABLE: Enables or disables a user. </li><li>SYSINFO: Specifies whether a user can query system information. </li></ul>
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- Information that you input is given in lowercase.
- \[ \] means optional input, excluding [] itself.
- | means one of a few options, excluding | itself.
- … means the item prior to it can be repeated multiple times.
- ... means the item prior to it can be repeated multiple times.
To better demonstrate the syntax, usage and rules of TDengine SQL, hereinafter it's assumed that there is a data set of data from electric meters. Each meter collects 3 data measurements: current, voltage, phase. The data model is shown below:
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Diagnostics for network connections can be executed between Linux/Windows/macOS.
Diagnostic steps：
Diagnostic steps:
1. If the port range to be diagnosed is being occupied by a `taosd` server process, please first stop `taosd.
2. On the server side, execute command `taos -n server -P <port> -l <pktlen>` to monitor the port range starting from the port specified by `-P` parameter with the role of "server".
3. On the client side, execute command `taos -n client -h <fqdn of server> -P <port> -l <pktlen>` to send a testing package to the specified server and port.
-l <pktlen\>： The size of the testing package, in bytes. The value range is [11, 64,000] and default value is 1,000.
-l <pktlen\>: The size of the testing package, in bytes. The value range is [11, 64,000] and default value is 1,000.
Please note that the package length must be same in the above 2 commands executed on server side and client side respectively.
Output of the server side for the example is below:
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- ** trying_interval ** : Specify interval between keep trying insert. Valid value is a positive number. Only valid when keep trying be enabled. Available with v3.0.9+.
- ** childtable_from and childtable_to ** : specify the child table range to create. The range is [childtable_from, childtable_to).
 
- ** continue_if_fail ** : allow the user to specify the reaction if the insertion failed.
- "continue_if_fail" : "no" // means taosBenchmark will exit if it fails to insert as default reaction behavior.
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