---
sidebar_label: Data Subscription
description: "The TDengine data subscription service automatically pushes data written in TDengine to subscribing clients."
title: Data Subscription
---
import Tabs from "@theme/Tabs";
import TabItem from "@theme/TabItem";
import Java from "./_sub_java.mdx";
import JavaWS from "./_sub_java_ws.mdx"
import Python from "./_sub_python.mdx";
import Go from "./_sub_go.mdx";
import Rust from "./_sub_rust.mdx";
import Node from "./_sub_node.mdx";
import CSharp from "./_sub_cs.mdx";
import CDemo from "./_sub_c.mdx";
TDengine provides data subscription and consumption interfaces similar to message queue products. These interfaces make it easier for applications to obtain data written to TDengine either in real time and to process data in the order that events occurred. This simplifies your time-series data processing systems and reduces your costs because it is no longer necessary to deploy a message queue product such as Kafka.
To use TDengine data subscription, you define topics like in Kafka. However, a topic in TDengine is based on query conditions for an existing supertable, table, or subtable - in other words, a SELECT statement. You can use SQL to filter data by tag, table name, column, or expression and then perform a scalar function or user-defined function on the data. Aggregate functions are not supported. This gives TDengine data subscription more flexibility than similar products. The granularity of data can be controlled on demand by applications, while filtering and preprocessing are handled by TDengine instead of the application layer. This implementation reduces the amount of data transmitted and the complexity of applications.
By subscribing to a topic, a consumer can obtain the latest data in that topic in real time. Multiple consumers can be formed into a consumer group that consumes messages together. Consumer groups enable faster speed through multi-threaded, distributed data consumption. Note that consumers in different groups that are subscribed to the same topic do not consume messages together. A single consumer can subscribe to multiple topics. If the data in a supertable is sharded across multiple vnodes, consumer groups can consume it much more efficiently than single consumers. TDengine also includes an acknowledgement mechanism that ensures at-least-once delivery in complicated environments where machines may crash or restart.
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: 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
The related schemas and APIs in various languages are described as follows:
```c
typedef struct tmq_t tmq_t;
typedef struct tmq_conf_t tmq_conf_t;
typedef struct tmq_list_t tmq_list_t;
typedef void(tmq_commit_cb(tmq_t *, int32_t code, void *param));
DLL_EXPORT tmq_list_t *tmq_list_new();
DLL_EXPORT int32_t tmq_list_append(tmq_list_t *, const char *);
DLL_EXPORT void tmq_list_destroy(tmq_list_t *);
DLL_EXPORT tmq_t *tmq_consumer_new(tmq_conf_t *conf, char *errstr, int32_t errstrLen);
DLL_EXPORT const char *tmq_err2str(int32_t code);
DLL_EXPORT int32_t tmq_subscribe(tmq_t *tmq, const tmq_list_t *topic_list);
DLL_EXPORT int32_t tmq_unsubscribe(tmq_t *tmq);
DLL_EXPORT TAOS_RES *tmq_consumer_poll(tmq_t *tmq, int64_t timeout);
DLL_EXPORT int32_t tmq_consumer_close(tmq_t *tmq);
DLL_EXPORT int32_t tmq_commit_sync(tmq_t *tmq, const TAOS_RES *msg);
DLL_EXPORT void tmq_commit_async(tmq_t *tmq, const TAOS_RES *msg, tmq_commit_cb *cb, void *param);
enum tmq_conf_res_t {
TMQ_CONF_UNKNOWN = -2,
TMQ_CONF_INVALID = -1,
TMQ_CONF_OK = 0,
};
typedef enum tmq_conf_res_t tmq_conf_res_t;
DLL_EXPORT tmq_conf_t *tmq_conf_new();
DLL_EXPORT tmq_conf_res_t tmq_conf_set(tmq_conf_t *conf, const char *key, const char *value);
DLL_EXPORT void tmq_conf_destroy(tmq_conf_t *conf);
DLL_EXPORT void tmq_conf_set_auto_commit_cb(tmq_conf_t *conf, tmq_commit_cb *cb, void *param);
```
For more information, see [C/C++ Connector](/reference/connector/cpp).
The following example is based on the smart meter table described in Data Models. For complete sample code, see the C language section below.
```java
void subscribe(Collection topics) throws SQLException;
void unsubscribe() throws SQLException;
Set subscription() throws SQLException;
ConsumerRecords poll(Duration timeout) throws SQLException;
void commitSync() throws SQLException;
void close() throws SQLException;
```
```python
class Consumer:
def subscribe(self, topics):
pass
def unsubscribe(self):
pass
def poll(self, timeout: float = 1.0):
pass
def assignment(self):
pass
def poll(self, timeout: float = 1.0):
pass
def close(self):
pass
def commit(self, message):
pass
```
```go
func NewConsumer(conf *tmq.ConfigMap) (*Consumer, error)
// rebalanceCb is reserved for compatibility purpose
func (c *Consumer) Subscribe(topic string, rebalanceCb RebalanceCb) error
// rebalanceCb is reserved for compatibility purpose
func (c *Consumer) SubscribeTopics(topics []string, rebalanceCb RebalanceCb) error
func (c *Consumer) Poll(timeoutMs int) tmq.Event
// tmq.TopicPartition is reserved for compatibility purpose
func (c *Consumer) Commit() ([]tmq.TopicPartition, error)
func (c *Consumer) Unsubscribe() error
func (c *Consumer) Close() error
```
```rust
impl TBuilder for TmqBuilder
fn from_dsn(dsn: D) -> Result
fn build(&self) -> Result
impl AsAsyncConsumer for Consumer
async fn subscribe, I: IntoIterator- + Send>(
&mut self,
topics: I,
) -> Result<(), Self::Error>;
fn stream(
&self,
) -> Pin<
Box<
dyn '_
+ Send
+ futures::Stream<
Item = Result<(Self::Offset, MessageSet), Self::Error>,
>,
>,
>;
async fn commit(&self, offset: Self::Offset) -> Result<(), Self::Error>;
async fn unsubscribe(self);
```
For more information, see [Crate taos](https://docs.rs/taos).
```js
function TMQConsumer(config)
function subscribe(topic)
function consume(timeout)
function subscription()
function unsubscribe()
function commit(msg)
function close()
```
```csharp
ConsumerBuilder(IEnumerable> config)
virtual IConsumer Build()
Consumer(ConsumerBuilder builder)
void Subscribe(IEnumerable topics)
void Subscribe(string topic)
ConsumeResult Consume(int millisecondsTimeout)
List Subscription()
void Unsubscribe()
void Commit(ConsumeResult consumerResult)
void Close()
```
## Insert Data into TDengine
A database including one supertable and two subtables is created as follows:
```sql
DROP DATABASE IF EXISTS 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");
INSERT INTO tmqdb.ctb0 VALUES(now, 0, 0, 'a0')(now+1s, 0, 0, 'a00');
INSERT INTO tmqdb.ctb1 VALUES(now, 1, 1, 'a1')(now+1s, 11, 11, 'a11');
```
## Create a Topic
The following SQL statement creates a topic in TDengine:
```sql
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
Syntax:
```sql
CREATE TOPIC topic_name as subquery
```
You can subscribe to a topic through a SELECT statement. Statements that specify columns, such as `SELECT *` and `SELECT ts, cl` are supported, as are filtering conditions and scalar functions. Aggregate functions and time window aggregation are not supported. Note:
- The schema of topics created in this manner is determined by the subscribed data.
- You cannot modify (`ALTER
MODIFY`) or delete (`ALTER DROP`) columns or tags that are used in a subscription or calculation.
- Columns added to a table after the subscription is created are not displayed in the results. Deleting columns will cause an error.
### Subscribe to a Supertable
Syntax:
```sql
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.
- 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
Syntax:
```sql
CREATE TOPIC topic_name [with meta] AS DATABASE db_name;
```
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
You configure the following parameters when creating a consumer:
| Parameter | Type | Description | Remarks |
| :----------------------------: | :-----: | -------------------------------------------------------- | ------------------------------------------- |
| `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 | `earliest`: subscribe from the earliest data, this is the default behavior; `latest`: subscribe from the latest data; or `none`: can't subscribe without committed offset|
| `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 |
| `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:
```c
/* Create consumer groups on demand (group.id) and enable automatic commits (enable.auto.commit),
an automatic commit interval (auto.commit.interval.ms), and a username (td.connect.user) and password (td.connect.pass) */
tmq_conf_t* conf = tmq_conf_new();
tmq_conf_set(conf, "enable.auto.commit", "true");
tmq_conf_set(conf, "auto.commit.interval.ms", "1000");
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, "msg.with.table.name", "true");
tmq_conf_set_auto_commit_cb(conf, tmq_commit_cb_print, NULL);
tmq_t* tmq = tmq_consumer_new(conf, NULL, 0);
tmq_conf_destroy(conf);
```
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 | |
Note: The `bootstrap.servers` parameter is used instead of `td.connect.ip` and `td.connect.port` to provide an interface that is consistent with Kafka.
```java
Properties properties = new Properties();
properties.setProperty("enable.auto.commit", "true");
properties.setProperty("auto.commit.interval.ms", "1000");
properties.setProperty("group.id", "cgrpName");
properties.setProperty("bootstrap.servers", "127.0.0.1:6030");
properties.setProperty("td.connect.user", "root");
properties.setProperty("td.connect.pass", "taosdata");
properties.setProperty("auto.offset.reset", "earliest");
properties.setProperty("msg.with.table.name", "true");
properties.setProperty("value.deserializer", "com.taos.example.MetersDeserializer");
TaosConsumer consumer = new TaosConsumer<>(properties);
/* value deserializer definition. */
import com.taosdata.jdbc.tmq.ReferenceDeserializer;
public class MetersDeserializer extends ReferenceDeserializer {
}
```
```go
conf := &tmq.ConfigMap{
"group.id": "test",
"auto.offset.reset": "earliest",
"td.connect.ip": "127.0.0.1",
"td.connect.user": "root",
"td.connect.pass": "taosdata",
"td.connect.port": "6030",
"client.id": "test_tmq_c",
"enable.auto.commit": "false",
"msg.with.table.name": "true",
}
consumer, err := NewConsumer(conf)
```
```rust
let mut dsn: Dsn = "taos://".parse()?;
dsn.set("group.id", "group1");
dsn.set("client.id", "test");
dsn.set("auto.offset.reset", "earliest");
let tmq = TmqBuilder::from_dsn(dsn)?;
let mut consumer = tmq.build()?;
```
```python
from taos.tmq import Consumer
# Syntax: `consumer = Consumer(configs)`
#
# Example:
consumer = Consumer({"group.id": "local", "td.connect.ip": "127.0.0.1"})
```
```js
// Create consumer groups on demand (group.id) and enable automatic commits (enable.auto.commit),
// an automatic commit interval (auto.commit.interval.ms), and a username (td.connect.user) and password (td.connect.pass)
let consumer = taos.consumer({
'enable.auto.commit': 'true',
'auto.commit.interval.ms','1000',
'group.id': 'tg2',
'td.connect.user': 'root',
'td.connect.pass': 'taosdata',
'auto.offset.reset','earliest',
'msg.with.table.name': 'true',
'td.connect.ip','127.0.0.1',
'td.connect.port','6030'
});
```
```csharp
using TDengineTMQ;
// Create consumer groups on demand (GourpID) and enable automatic commits (EnableAutoCommit),
// an automatic commit interval (AutoCommitIntervalMs), and a username (TDConnectUser) and password (TDConnectPasswd)
var cfg = new ConsumerConfig
{
EnableAutoCommit = "true"
AutoCommitIntervalMs = "1000"
GourpId = "TDengine-TMQ-C#",
TDConnectUser = "root",
TDConnectPasswd = "taosdata",
AutoOffsetReset = "earliest"
MsgWithTableName = "true",
TDConnectIp = "127.0.0.1",
TDConnectPort = "6030"
};
var consumer = new ConsumerBuilder(cfg).Build();
```
A consumer group is automatically created when multiple consumers are configured with the same consumer group ID.
## Subscribe to a Topic
A single consumer can subscribe to multiple topics.
```c
// Create a list of subscribed topics
tmq_list_t* topicList = tmq_list_new();
tmq_list_append(topicList, "topicName");
// Enable subscription
tmq_subscribe(tmq, topicList);
tmq_list_destroy(topicList);
```
```java
List topics = new ArrayList<>();
topics.add("tmq_topic");
consumer.subscribe(topics);
```
```go
err = consumer.Subscribe("example_tmq_topic", nil)
if err != nil {
panic(err)
}
```
```rust
consumer.subscribe(["tmq_meters"]).await?;
```
```python
consumer.subscribe(['topic1', 'topic2'])
```
```js
// Create a list of subscribed topics
let topics = ['topic_test']
// Enable subscription
consumer.subscribe(topics);
```
```csharp
// Create a list of subscribed topics
List topics = new List();
topics.add("tmq_topic");
// Enable subscription
consumer.Subscribe(topics);
```
## Consume messages
The following code demonstrates how to consume the messages in a queue.
```c
## Consume data
while (running) {
TAOS_RES* msg = tmq_consumer_poll(tmq, timeOut);
msg_process(msg);
}
```
The `while` loop obtains a message each time it calls `tmq_consumer_poll()`. This message is exactly the same as the result returned by a query, and the same deserialization API can be used on it.
```java
while(running){
ConsumerRecords meters = consumer.poll(Duration.ofMillis(100));
for (Meters meter : meters) {
processMsg(meter);
}
}
```
```go
for {
ev := consumer.Poll(0)
if ev != nil {
switch e := ev.(type) {
case *tmqcommon.DataMessage:
fmt.Println(e.Value())
case tmqcommon.Error:
fmt.Fprintf(os.Stderr, "%% Error: %v: %v\n", e.Code(), e)
panic(e)
}
consumer.Commit()
}
}
```
```rust
{
let mut stream = consumer.stream();
while let Some((offset, message)) = stream.try_next().await? {
// get information from offset
// the topic
let topic = offset.topic();
// the vgroup id, like partition id in kafka.
let vgroup_id = offset.vgroup_id();
println!("* in vgroup id {vgroup_id} of topic {topic}\n");
if let Some(data) = message.into_data() {
while let Some(block) = data.fetch_raw_block().await? {
// one block for one table, get table name if needed
let name = block.table_name();
let records: Vec = block.deserialize().try_collect()?;
println!(
"** table: {}, got {} records: {:#?}\n",
name.unwrap(),
records.len(),
records
);
}
}
consumer.commit(offset).await?;
}
}
```
```python
while True:
res = consumer.poll(100)
if not res:
continue
err = res.error()
if err is not None:
raise err
val = res.value()
for block in val:
print(block.fetchall())
```
```js
while(true){
msg = consumer.consume(200);
// process message(consumeResult)
console.log(msg.topicPartition);
console.log(msg.block);
console.log(msg.fields)
}
```
```csharp
## Consume data
while (true)
{
var consumerRes = consumer.Consume(100);
// process ConsumeResult
ProcessMsg(consumerRes);
consumer.Commit(consumerRes);
}
```
## Close the consumer
After message consumption is finished, the consumer is unsubscribed.
```c
/* Unsubscribe */
tmq_unsubscribe(tmq);
/* Close consumer object */
tmq_consumer_close(tmq);
```
```java
/* Unsubscribe */
consumer.unsubscribe();
/* Close consumer */
consumer.close();
```
```go
/* Unsubscribe */
_ = consumer.Unsubscribe()
/* Close consumer */
_ = consumer.Close()
```
```rust
consumer.unsubscribe().await;
```
```py
# Unsubscribe
consumer.unsubscribe()
# Close consumer
consumer.close()
```
```js
consumer.unsubscribe();
consumer.close();
```
```csharp
// Unsubscribe
consumer.Unsubscribe();
// Close consumer
consumer.Close();
```
## Delete a Topic
You can delete topics that are no longer useful. Note that you must unsubscribe all consumers from a topic before deleting it.
```sql
/* Delete topic/
DROP TOPIC topic_name;
```
## Check Status
1. Query all existing topics.
```sql
SHOW TOPICS;
```
2. Query the status and subscribed topics of all consumers.
```sql
SHOW CONSUMERS;
```
3. Query the relationships between consumers and vgroups.
```sql
SHOW SUBSCRIPTIONS;
```
## Examples
The following section shows sample code in various languages.