BackTDengine connectors
-TDengine provides many connectors for development, including C/C++, JAVA, Python, RESTful, Go, Node.JS, etc.
-C/C++ API
-C/C++ APIs are similar to the MySQL APIs. Applications should include TDengine head file taos.h to use C/C++ APIs by adding the following line in code:
-#include <taos.h>
-Make sure TDengine library libtaos.so is installed and use -ltaos option to link the library when compiling. The return values of all APIs are -1 or NULL for failure.
-C/C++ sync API
-Sync APIs are those APIs waiting for responses from the server after sending a request. TDengine has the following sync APIs:
-
-TAOS *taos_connect(char *ip, char *user, char *pass, char *db, int port)
-Open a connection to a TDengine server. The parameters are ip (IP address of the server), user (username to login), pass (password to login), db (database to use after connection) and port (port number to connect). The parameter db can be NULL for no database to use after connection. Otherwise, the database should exist before connection or a connection error is reported. The handle returned by this API should be kept for future use.
void taos_close(TAOS *taos)
-Close a connection to a TDengine server by the handle returned by taos_connect`
int taos_query(TAOS *taos, char *sqlstr)
-The API used to run a SQL command. The command can be DQL or DML. The parameter taos is the handle returned by taos_connect. Return value -1 means failure.
TAOS_RES *taos_use_result(TAOS *taos)
-Use the result after running taos_query. The handle returned should be kept for future fetch.
TAOS_ROW taos_fetch_row(TAOS_RES *res)
-Fetch a row of return results through res, the handle returned by taos_use_result.
int taos_num_fields(TAOS_RES *res)
-Get the number of fields in the return result.
TAOS_FIELD *taos_fetch_fields(TAOS_RES *res)
-Fetch the description of each field. The description includes the property of data type, field name, and bytes. The API should be used with taos_num_fields to fetch a row of data.
void taos_free_result(TAOS_RES *res)
-Free the resources used by a result set. Make sure to call this API after fetching results or memory leak would happen.
void taos_init()
-Initialize the environment variable used by TDengine client. The API is not necessary since it is called int taos_connect by default.
char *taos_errstr(TAOS *taos)
-Return the reason of the last API call failure. The return value is a string.
int *taos_errno(TAOS *taos)
-Return the error code of the last API call failure. The return value is an integer.
int taos_options(TSDB_OPTION option, const void * arg, ...)
-Set client options. The parameter option supports values of TSDB_OPTION_CONFIGDIR (configuration directory), TSDB_OPTION_SHELL_ACTIVITY_TIMER, TSDB_OPTION_LOCALE (client locale) and TSDB_OPTION_TIMEZONE (client timezone).
-The 12 APIs are the most important APIs frequently used. Users can check taos.h file for more API information.
-Note: The connection to a TDengine server is not multi-thread safe. So a connection can only be used by one thread.
-C/C++ async API
-In addition to sync APIs, TDengine also provides async APIs, which are more efficient. Async APIs are returned right away without waiting for a response from the server, allowing the application to continute with other tasks without blocking. So async APIs are more efficient, especially useful when in a poor network.
-All async APIs require callback functions. The callback functions have the format:
-void fp(void *param, TAOS_RES * res, TYPE param3)
-The first two parameters of the callback function are the same for all async APIs. The third parameter is different for different APIs. Generally, the first parameter is the handle provided to the API for action. The second parameter is a result handle.
-
-void taos_query_a(TAOS *taos, char *sqlstr, void (*fp)(void *param, TAOS_RES *, int code), void *param);
-The async query interface. taos is the handle returned by taos_connect interface. sqlstr is the SQL command to run. fp is the callback function. param is the parameter required by the callback function. The third parameter of the callback function code is 0 (for success) or a negative number (for failure, call taos_errstr to get the error as a string). Applications mainly handle with the second parameter, the returned result set.
void taos_fetch_rows_a(TAOS_RES *res, void (*fp)(void *param, TAOS_RES *, int numOfRows), void *param);
-The async API to fetch a batch of rows, which should only be used with a taos_query_a call. The parameter res is the result handle returned by taos_query_a. fp is the callback function. param is a user-defined structure to pass to fp. The parameter numOfRows is the number of result rows in the current fetch cycle. In the callback function, applications should call taos_fetch_row to get records from the result handle. After getting a batch of results, applications should continue to call taos_fetch_rows_a API to handle the next batch, until the numOfRows is 0 (for no more data to fetch) or -1 (for failure).
void taos_fetch_row_a(TAOS_RES *res, void (*fp)(void *param, TAOS_RES *, TAOS_ROW row), void *param);
-The async API to fetch a result row. res is the result handle. fp is the callback function. param is a user-defined structure to pass to fp. The third parameter of the callback function is a single result row, which is different from that of taos_fetch_rows_a API. With this API, it is not necessary to call taos_fetch_row to retrieve each result row, which is handier than taos_fetch_rows_a but less efficient.
-Applications may apply operations on multiple tables. However, it is important to make sure the operations on the same table are serialized. That means after sending an insert request in a table to the server, no operations on the table are allowed before a response is received.
-C/C++ continuous query interface
-TDengine provides APIs for continuous query driven by time, which run queries periodically in the background. There are only two APIs:
-
-TAOS_STREAM *taos_open_stream(TAOS *taos, char *sqlstr, void (*fp)(void *param, TAOS_RES *, TAOS_ROW row), int64_t stime, void *param, void (*callback)(void *));
-The API is used to create a continuous query.
taos: the connection handle returned by taos_connect.
sqlstr: the SQL string to run. Only query commands are allowed.
fp: the callback function to run after a query
param: a parameter passed to fp
stime: the time of the stream starts in the form of epoch milliseconds. If 0 is given, the start time is set as the current time.
callback: a callback function to run when the continuous query stops automatically.
-The API is expected to return a handle for success. Otherwise, a NULL pointer is returned.
void taos_close_stream (TAOS_STREAM *tstr)
-Close the continuous query by the handle returned by taos_open_stream. Make sure to call this API when the continuous query is not needed anymore.
-C/C++ subscription API
-For the time being, TDengine supports subscription on one table. It is implemented through periodic pulling from a TDengine server.
-
-TAOS_SUB *taos_subscribe(char *host, char *user, char *pass, char *db, char *table, long time, int mseconds)
-The API is used to start a subscription session by given a handle. The parameters required are host (IP address of a TDenginer server), user (username), pass (password), db (database to use), table (table name to subscribe), time (start time to subscribe, 0 for now), mseconds (pulling period). If failed to open a subscription session, a NULL pointer is returned.
TAOS_ROW taos_consume(TAOS_SUB *tsub)
-The API used to get the new data from a TDengine server. It should be put in an infinite loop. The parameter tsub is the handle returned by taos_subscribe. If new data are updated, the API will return a row of the result. Otherwise, the API is blocked until new data arrives. If NULL pointer is returned, it means an error occurs.
void taos_unsubscribe(TAOS_SUB *tsub)
-Stop a subscription session by the handle returned by taos_subscribe.
int taos_num_fields(TAOS_SUB *tsub)
-The API used to get the number of fields in a row.
TAOS_FIELD *taos_fetch_fields(TAOS_RES *res)
-The API used to get the description of each column.
-Java Connector
-JDBC Interface
-TDengine provides a JDBC driver taos-jdbcdriver-x.x.x.jar for Enterprise Java developers. TDengine's JDBC Driver is implemented as a subset of the standard JDBC 3.0 Specification and supports the most common Java development frameworks. The driver is currently not published to the online dependency repositories such as Maven Center Repository, and users should manually add the .jar file to their local dependency repository.
-Please note the JDBC driver itself relies on a native library written in C. On a Linux OS, the driver relies on a libtaos.so native library, where .so stands for "Shared Object". After the successful installation of TDengine on Linux, libtaos.so should be automatically copied to /usr/local/lib/taos and added to the system's default search path. On a Windows OS, the driver relies on a taos.dll native library, where .dll stands for "Dynamic Link Library". After the successful installation of the TDengine client on Windows, the taos-jdbcdriver.jar file can be found in C:/TDengine/driver/JDBC; the taos.dll file can be found in C:/TDengine/driver/C and should have been automatically copied to the system's searching path C:/Windows/System32.
-Developers can refer to the Oracle's official JDBC API documentation for detailed usage on classes and methods. However, there are some differences of connection configurations and supported methods in the driver implementation between TDengine and traditional relational databases.
-For database connections, TDengine's JDBC driver has the following configurable parameters in the JDBC URL. The standard format of a TDengine JDBC URL is:
-jdbc:TSDB://{host_ip}:{port}/{database_name}?[user={user}|&password={password}|&charset={charset}|&cfgdir={config_dir}|&locale={locale}|&timezone={timezone}]
-where {} marks the required parameters and [] marks the optional. The usage of each parameter is pretty straightforward:
-
-- user - login user name for TDengine; by default, it's
root
-- password - login password; by default, it's
taosdata
-- charset - the client-side charset; by default, it's the operation system's charset
-- cfgdir - the directory of TDengine client configuration file; by default it's
/etc/taos on Linux and C:\TDengine/cfg on Windows
-- locale - the language environment of TDengine client; by default, it's the operation system's locale
-- timezone - the timezone of the TDengine client; by default, it's the operation system's timezone
-
-All parameters can be configured at the time when creating a connection using the java.sql.DriverManager class, for example:
-import java.sql.Connection;
-import java.sql.DriverManager;
-import java.util.Properties;
-import com.taosdata.jdbc.TSDBDriver;
-
-public Connection getConn() throws Exception{
- Class.forName("com.taosdata.jdbc.TSDBDriver");
- String jdbcUrl = "jdbc:TAOS://127.0.0.1:0/db?user=root&password=taosdata";
- Properties connProps = new Properties();
- connProps.setProperty(TSDBDriver.PROPERTY_KEY_USER, "root");
- connProps.setProperty(TSDBDriver.PROPERTY_KEY_PASSWORD, "taosdata");
- connProps.setProperty(TSDBDriver.PROPERTY_KEY_CONFIG_DIR, "/etc/taos");
- connProps.setProperty(TSDBDriver.PROPERTY_KEY_CHARSET, "UTF-8");
- connProps.setProperty(TSDBDriver.PROPERTY_KEY_LOCALE, "en_US.UTF-8");
- connProps.setProperty(TSDBDriver.PROPERTY_KEY_TIMEZONE, "UTC-8");
- Connection conn = DriverManager.getConnection(jdbcUrl, connProps);
- return conn;
-}
-Except cfgdir, all the parameters listed above can also be configured in the configuration file. The properties specified when calling DriverManager.getConnection() has the highest priority among all configuration methods. The JDBC URL has the second-highest priority, and the configuration file has the lowest priority. The explicitly configured parameters in a method with higher priorities always overwrite that same parameter configured in methods with lower priorities. For example, if charset is explicitly configured as "UTF-8" in the JDBC URL and "GKB" in the taos.cfg file, then "UTF-8" will be used.
-Although the JDBC driver is implemented following the JDBC standard as much as possible, there are major differences between TDengine and traditional databases in terms of data models that lead to the differences in the driver implementation. Here is a list of head-ups for developers who have plenty of experience on traditional databases but little on TDengine:
-
-- TDengine does NOT support updating or deleting a specific record, which leads to some unsupported methods in the JDBC driver
-- TDengine currently does not support
join or union operations, and thus, is lack of support for associated methods in the JDBC driver
-- TDengine supports batch insertions which are controlled at the level of SQL statement writing instead of API calls
-- TDengine doesn't support nested queries and neither does the JDBC driver. Thus for each established connection to TDengine, there should be only one open result set associated with it
-
-All the error codes and error messages can be found in TSDBError.java . For a more detailed coding example, please refer to the demo project JDBCDemo in TDengine's code examples.
-Python Connector
-Pre-requirement
-TDengine installed, TDengine-client installed if on Windows
-python 2.7 or >= 3.4
-pip installed
-Installation
-Linux
-Users can find python client packages in our source code directory src/connector/python. There are two directories corresponding to two python versions. Please choose the correct package to install. Users can use pip command to install:
-pip install src/connector/python/linux/python2/
-or
-pip install src/connector/python/linux/python3/
-Windows
-Assumed the Windows TDengine client has been installed , copy the file "C:\TDengine\driver\taos.dll" to the folder "C:\windows\system32", and then enter the cmd Windows command interface
-cd C:\TDengine\connector\python\windows
-pip install python2\
-or
-cd C:\TDengine\connector\python\windows
-pip install python3\
-* If pip command is not installed on the system, users can choose to install pip or just copy the taos directory in the python client directory to the application directory to use.
-Usage
-Examples
-import TDengine module at first:
-import taos
-get the connection
-
-conn = taos.connect(host="127.0.0.1", user="root", password="taosdata", config="/etc/taos")
-c1 = conn.cursor()
-
-* host is the IP of TDengine server, and config is the directory where exists the TDengine client configure file
-insert records into the database
-
-import datetime
-
-# create a database
-c1.execute('create database db')
-c1.execute('use db')
-# create a table
-c1.execute('create table tb (ts timestamp, temperature int, humidity float)')
-# insert a record
-start_time = datetime.datetime(2019, 11, 1)
-affected_rows = c1.execute('insert into tb values (\'%s\', 0, 0.0)' %start_time)
-# insert multiple records in a batch
-time_interval = datetime.timedelta(seconds=60)
-sqlcmd = ['insert into tb values']
-for irow in range(1,11):
- start_time += time_interval
- sqlcmd.append('(\'%s\', %d, %f)' %(start_time, irow, irow*1.2))
-affected_rows = c1.execute(' '.join(sqlcmd))
-
-query the database
-
-c1.execute('select * from tb')
-# fetch all returned results
-data = c1.fetchall()
-# data is a list of returned rows with each row being a tuple
-numOfRows = c1.rowcount
-numOfCols = c1.descriptions
-for irow in range(numOfRows):
- print("Row%d: ts=%s, temperature=%d, humidity=%f" %(irow, data[irow][0], data[irow][1],data[irow][2])
-
-# use the cursor as an iterator to retrieve all returned results
-c1.execute('select * from tb')
-for data in c1:
- print("ts=%s, temperature=%d, humidity=%f" %(data[0], data[1],data[2])
-
-c1.close()
-conn.close()
-
Help information
-Users can get module information from Python help interface or refer to our [python code example](). We list the main classes and methods below:
-
-TaosConnection class
-Run help(taos.TaosConnection) in python terminal for details.
TaosCursor class
-Run help(taos.TaosCursor) in python terminal for details.
connect method
-Open a connection. Run help(taos.connect) in python terminal for details.
-RESTful Connector
-TDengine also provides RESTful API to satisfy developing on different platforms. Unlike other databases, TDengine RESTful API applies operations to the database through the SQL command in the body of HTTP POST request. What users are required to provide is just a URL.
-For the time being, TDengine RESTful API uses a \ generated from username and password for identification. Safer identification methods will be provided in the future.
-HTTP URL encoding
-To use TDengine RESTful API, the URL should have the following encoding format:
-http://<ip>:<PORT>/rest/sql
-
-- ip: IP address of any node in a TDengine cluster
-- PORT: TDengine HTTP service port. It is 6020 by default.
-
-For example, the URL encoding http://192.168.0.1:6020/rest/sql used to send HTTP request to a TDengine server with IP address as 192.168.0.1.
-It is required to add a token in an HTTP request header for identification.
-Authorization: Basic <TOKEN>
-The HTTP request body contains the SQL command to run. If the SQL command contains a table name, it should also provide the database name it belongs to in the form of <db_name>.<tb_name>. Otherwise, an error code is returned.
-For example, use curl command to send a HTTP request:
-curl -H 'Authorization: Basic <TOKEN>' -d '<SQL>' <ip>:<PORT>/rest/sql
-or use
-curl -u username:password -d '<SQL>' <ip>:<PORT>/rest/sql
-where TOKEN is the encryted string of {username}:{password} using the Base64 algorithm, e.g. root:taosdata will be encoded as cm9vdDp0YW9zZGF0YQ==
-HTTP response
-The HTTP resonse is in JSON format as below:
-{
- "status": "succ",
- "head": ["column1","column2", …],
- "data": [
- ["2017-12-12 23:44:25.730", 1],
- ["2017-12-12 22:44:25.728", 4]
- ],
- "rows": 2
-}
-Specifically,
-
-- status: the result of the operation, success or failure
-- head: description of returned result columns
-- data: the returned data array. If no data is returned, only an affected_rows field is listed
-- rows: the number of rows returned
-
-Example
-
-The return value is like:
-{
- "status": "succ",
- "head": ["column1","column2","column3"],
- "data": [
- ["2017-12-12 23:44:25.730", 1, 2.3],
- ["2017-12-12 22:44:25.728", 4, 5.6]
- ],
- "rows": 2
-}
-
-Use HTTP to create a database：
-curl -H 'Authorization: Basic cm9vdDp0YW9zZGF0YQ==' -d 'create database demo' 192.168.0.1:6020/rest/sql
-The return value should be:
-{
- "status": "succ",
- "head": ["affected_rows"],
- "data": [[1]],
- "rows": 1,
-}
-Go Connector
-TDengine also provides a Go client package named taosSql for users to access TDengine with Go. The package is in /usr/local/taos/connector/go/src/taosSql by default if you installed TDengine. Users can copy the directory /usr/local/taos/connector/go/src/taosSql to the src directory of your project and import the package in the source code for use.
-import (
- "database/sql"
- _ "taosSql"
-)
-The taosSql package is in cgo form, which calls TDengine C/C++ sync interfaces. So a connection is allowed to be used by one thread at the same time. Users can open multiple connections for multi-thread operations.
-Please refer the the demo code in the package for more information.
-Node.js Connector
-TDengine also provides a node.js connector package that is installable through npm. The package is also in our source code at src/connector/nodejs/. The following instructions are also available here
-To get started, just type in the following to install the connector through npm.
-npm install td-connector
-It is highly suggested you use npm. If you don't have it installed, you can also just copy the nodejs folder from src/connector/nodejs/ into your node project folder.
-To interact with TDengine, we make use of the node-gyp library. To install, you will need to install the following depending on platform (the following instructions are quoted from node-gyp)
-On Unix
-
-python (v2.7 recommended, v3.x.x is not supported)make- A proper C/C++ compiler toolchain, like GCC
-
-On macOS
-
-python (v2.7 recommended, v3.x.x is not supported) (already installed on macOS)
Xcode
You also need to install the
-Command Line Tools
-via Xcode. You can find this under the menu
-Xcode -> Preferences -> Locations
-(or by running
-xcode-select --install
-in your Terminal)
-
-- This step will install
gcc and the related toolchain containing make
-On Windows
-Option 1
-Install all the required tools and configurations using Microsoft's windows-build-tools using npm install --global --production windows-build-tools from an elevated PowerShell or CMD.exe (run as Administrator).
-Option 2
-Install tools and configuration manually:
-
-- Install Visual C++ Build Environment: Visual Studio Build Tools (using "Visual C++ build tools" workload) or Visual Studio 2017 Community (using the "Desktop development with C++" workload)
-- Install Python 2.7 (
v3.x.x is not supported), and run npm config set python python2.7 (or see below for further instructions on specifying the proper Python version and path.)
-- Launch cmd,
npm config set msvs_version 2017
-
-If the above steps didn't work for you, please visit Microsoft's Node.js Guidelines for Windows for additional tips.
-To target native ARM64 Node.js on Windows 10 on ARM, add the components "Visual C++ compilers and libraries for ARM64" and "Visual C++ ATL for ARM64".
-Usage
-The following is a short summary of the basic usage of the connector, the full api and documentation can be found here
-Connection
-To use the connector, first require the library td-connector. Running the function taos.connect with the connection options passed in as an object will return a TDengine connection object. The required connection option is host, other options if not set, will be the default values as shown below.
-A cursor also needs to be initialized in order to interact with TDengine from Node.js.
-const taos = require('td-connector');
-var conn = taos.connect({host:"127.0.0.1", user:"root", password:"taosdata", config:"/etc/taos",port:0})
-var cursor = conn.cursor(); // Initializing a new cursor
-To close a connection, run
-conn.close();
-Queries
-We can now start executing simple queries through the cursor.query function, which returns a TaosQuery object.
-var query = cursor.query('show databases;')
-We can get the results of the queries through the query.execute() function, which returns a promise that resolves with a TaosResult object, which contains the raw data and additional functionalities such as pretty printing the results.
-var promise = query.execute();
-promise.then(function(result) {
- result.pretty(); //logs the results to the console as if you were in the taos shell
-});
-You can also query by binding parameters to a query by filling in the question marks in a string as so. The query will automatically parse what was binded and convert it to the proper format for use with TDengine
-var query = cursor.query('select * from meterinfo.meters where ts <= ? and areaid = ?;').bind(new Date(), 5);
-query.execute().then(function(result) {
- result.pretty();
-})
-The TaosQuery object can also be immediately executed upon creation by passing true as the second argument, returning a promise instead of a TaosQuery.
-var promise = cursor.query('select * from meterinfo.meters where v1 = 30;', true)
-promise.then(function(result) {
- result.pretty();
-})
-Async functionality
-Async queries can be performed using the same functions such as cursor.execute, cursor.query, but now with _a appended to them.
-Say you want to execute an two async query on two seperate tables, using cursor.query_a, you can do that and get a TaosQuery object, which upon executing with the execute_a function, returns a promise that resolves with a TaosResult object.
-var promise1 = cursor.query_a('select count(*), avg(v1), avg(v2) from meter1;').execute_a()
-var promise2 = cursor.query_a('select count(*), avg(v1), avg(v2) from meter2;').execute_a();
-promise1.then(function(result) {
- result.pretty();
-})
-promise2.then(function(result) {
- result.pretty();
-})
-Example
-An example of using the NodeJS connector to create a table with weather data and create and execute queries can be found here (The preferred method for using the connector)
-An example of using the NodeJS connector to achieve the same things but without all the object wrappers that wrap around the data returned to achieve higher functionality can be found here
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