Realtime Compute for Apache Flink:Simple Log Service connector

Features

Prerequisites

A project and a Logstore are created. For more information, see the :Create a project and a Logstore" section of the Getting Started topic.

Limits

• Only Realtime Compute for Apache Flink that uses Ververica Runtime (VVR) 2.0.0 or later supports the Simple Log Service connector.

• The Simple Log Service connector supports only the at-least-once semantics.

• Only Realtime Compute for Apache Flink that uses VVR 4.0.13 or later supports automatic failovers of deployments due to the change of shard numbers.

• We recommended that you do not set the deployment parallelism for a source node to a value greater than the number of shards. If the deployment parallelism for a source node is greater than the number of shards, resources may be wasted. In Realtime Compute for Apache Flink that uses VVR 8.0.5 or earlier, if the number of shards changes, automatic failovers of deployments may become invalid and specific shards may not be consumed.

Syntax

CREATE TABLE sls_table(
  a INT,
  b INT,
  c VARCHAR
) WITH (
  'connector' = 'sls',
  'endPoint' = '<yourEndPoint>',
  'project' = '<yourProjectName>',
  'logStore' = '<yourLogStoreName>',
  'accessId' = '${secret_values.ak_id}',
  'accessKey' = '${secret_values.ak_secret}'
);

Parameters in the WITH clause

• Common parameters

  Parameter	Description	Data type	Required	Default value	Remarks
  connector	The type of the table.	STRING	Yes	None	Set the value to sls.
  endPoint	The endpoint of Simple Log Service.	STRING	Yes	None	Enter the internal endpoint of Simple Log Service. For more information, see Endpoints. Note By default, Realtime Compute for Apache Flink cannot access the Internet. Alibaba Cloud provides NAT gateways to enable the communication between virtual private clouds (VPCs) and the Internet. For more information, see Console operations. We recommend that you do not access Simple Log Service over the Internet. If you want to access Simple Log Service over the Internet, use HTTPS and enable the global acceleration feature. For more information, Use the transfer acceleration feature.
  project	The name of the Simple Log Service project.	STRING	Yes	None	N/A
  logStore	The name of a Logstore or Metricstore of Simple Log Service.	STRING	Yes	None	Data in a Logstore is consumed in the same way as in a Metricstore.
  accessId	The AccessKey ID of your Alibaba Cloud account.	STRING	Yes	None	For more information, see the "How do I view information about the AccessKey ID and AccessKey secret of the account?" section of the Reference topic. Important To protect your AccessKey pair, we recommend that you configure the AccessKey ID by using the key management method. For more information, see Manage variables and keys.
  accessKey	The AccessKey secret of your Alibaba Cloud account.	STRING	Yes	None	For more information, see the "How do I view information about the AccessKey ID and AccessKey secret of the account?" section of the Reference topic. Important To protect your AccessKey pair, we recommend that you configure the AccessKey secret by using the key management method. For more information, see Manage variables and keys.

• Parameters only for source tables

  Parameter	Description	Data type	Required	Default value	Remarks
  enableNewSource	Specifies whether to use the FLIP-27 refactor source interface.	BOOLEAN	No	false	The FLIP-27 refactor source interface automatically adapts to shard changes. This ensures that shards are evenly distributed across all the data sources. Note Only Realtime Compute for Apache Flink that uses VVR 8.0.9 or later supports this parameter. Important The deployment cannot be restored from a specific state after the value of this parameter changes. You can configure the consumerGroup parameter to start the deployment. When the deployment consumes data of Simple Log Service, Realtime Compute for Apache Flink records the current consumer offset in a Simple Log Service consumer group. In this case, you can set the consumeFromCheckpoint parameter to true and start the deployment without states. This way, the deployment resumes consumption from the current consumer offset.
  shardDiscoveryIntervalMs	The interval at which shard changes are dynamically detected. Unit: milliseconds.	LONG	No	60000	If you set this parameter to a negative value, the dynamic detection feature can be disabled. Note This parameter takes effect only if the enableNewSource parameter is set to true. Only Realtime Compute for Apache Flink that uses VVR 8.0.9 or later supports this parameter.
  startupMode	The startup mode of the source table.	STRING	No	timestamp	Valid values: timestamp: Logs are consumed from the specified start time. This is the default value. latest: Logs are consumed from the latest offset. earliest: Logs are consumed from the earliest offset. Note If you set the consumeFromCheckpoint parameter to true, logs are consumed from a checkpoint stored in the specified consumer group. The startup mode specified by this parameter does not take effect.
  startTime	The time at which logs start to be consumed.	STRING	No	Current time	Format: yyyy-MM-dd hh:mm:ss. This parameter takes effect only if the startupMode parameter is set to timestamp. Note The startTime and stopTime parameters are configured based on the __receive_time__ attribute field in a Simple Log Service source table but are not based on the __timestamp__ attribute field.
  stopTime	The time at which log consumption is stopped.	STRING	No	None	Format: yyyy-MM-dd hh:mm:ss. Note If you want Realtime Compute for Apache Flink to exit after log consumption is complete, you must configure the exitAfterFinish parameter together with this parameter and set the exitAfterFinish parameter to true.
  consumerGroup	The name of the consumer group.	STRING	No	None	A consumer group records the consumption progress. You can specify a custom consumer group name. The format of the name is not fixed. Note A consumer group cannot be shared by multiple deployments for collaborative consumption. We recommend that you specify different consumer groups for different Realtime Compute for Apache Flink deployments. If you specify the same consumer group for different Realtime Compute for Apache Flink deployments, all data is consumed. When Realtime Compute for Apache Flink consumes data of Simple Log Service, the data is not sharded in a Simple Log Service consumer group. Therefore, if the deployments share the same consumer group, all messages in the consumer group are consumed by each deployment.
  consumeFromCheckpoint	Specifies whether to consume logs from the checkpoint that is stored in the specified consumer group.	STRING	No	false	Valid values: true: If you set this parameter to true, you must specify a consumer group. After you specify a consumer group, Realtime Compute for Apache Flink consumes logs from the checkpoint that is stored in the consumer group. If no checkpoint exists in the consumer group, Realtime Compute for Apache Flink consumes logs from the time specified by the startTime parameter. false: Realtime Compute for Apache Flink does not consume logs from the checkpoint that is stored in the specified consumer group. This is the default value. Note Only Realtime Compute for Apache Flink that uses VVR 6.0.5 or later supports this parameter.
  maxRetries	The number of retries that are allowed when data fails to be read from Simple Log Service.	STRING	No	3	N/A
  batchGetSize	The number of log groups from which data is read in a request.	STRING	No	100	The value of the batchGetSize parameter cannot exceed 1000. Otherwise, an error is returned.
  exitAfterFinish	Specifies whether Realtime Compute for Apache Flink exits after data consumption is complete.	STRING	No	false	Valid values: true: Realtime Compute for Apache Flink exits after data consumption is complete. false: Realtime Compute for Apache Flink does not exit after data consumption is complete. This is the default value. Note Only Realtime Compute for Apache Flink that uses VVR 4.0.13 or later supports this parameter.
  query	The query statement that is used to preprocess data before data consumption in Simple Log Service.	STRING	No	None	If you configure the query parameter, Realtime Compute for Apache Flink can filter out data from Simple Log Service before Realtime Compute for Apache Flink consumes data in Simple Log Service. This helps prevent Realtime Compute for Apache Flink from consuming all data in Simple Log Service. This reduces costs and improves data processing efficiency. For example, if you execute the 'query' = '*| where request_method = ''GET''' statement, Realtime Compute for Apache Flink matches the data whose value of the request_method field is equal to the value of the GET clause before Realtime Compute for Apache Flink reads data from a Logstore of Simple Log Service. Note Simple Log Service Processing Language (SPL) is required if you execute the query statement to preprocess data. For more information, see SPL overview. Important Only Realtime Compute for Apache Flink that uses VVR 8.0.1 or later supports this parameter. For more information about the regions in which Simple Log Service supports this feature, see Consume logs based on rules. This feature is free of charge in public preview phase. You may be charged for Simple Log Service in the future. For more information, see the "Billing" section of the Consume logs based on rules topic.

• Parameters only for result tables

  Parameter	Description	Data type	Required	Default value	Remarks
  topicField	Specifies a field name. The value of this parameter overwrites the value of the __topic__ attribute field to indicate the topic of the log.	STRING	No	None	The value of this parameter must be an existing field in the table.
  timeField	Specifies a field name. The value of this parameter overwrites the value of the __timestamp__ attribute field to indicate the log write time.	STRING	No	Current time	The value of this parameter must be an existing field of the INT type in the table. If no field is specified, the current time is used by default.
  sourceField	Specifies a field name. The value of this parameter overwrites the value of the __source__ attribute field to indicate the origin of the log. For example, the value is the IP address of the machine that generates the log.	STRING	No	None	The value of this parameter must be an existing field in the table.
  partitionField	Specifies a field name. A hash value is calculated based on the value of this parameter when data is written to Simple Log Service. Data that includes the same hash value is written to the same shard.	STRING	No	None	If you do not specify this parameter, each data entry is randomly written to an available shard.
  buckets	The number of buckets that are regrouped based on the hash value when the partitionField parameter is specified.	STRING	No	64	Valid values: [1,256]. The value of this parameter must be an integer power of 2. The number of buckets must be greater than or equal to the number of shards. Otherwise, no data is written to specific shards. Note Only Realtime Compute for Apache Flink that uses VVR 6.0.5 or later supports this parameter.
  flushIntervalMs	The interval at which data writing is triggered.	STRING	No	2000	Unit: milliseconds.
  writeNullProperties	Specifies whether to write null values as empty strings to Simple Log Service.	BOOLEAN	No	true	Valid values: true: Null values are written as empty strings to Simple Log Service. This is the default value. false: Null values are not written to Simple Log Service. Note Only Realtime Compute for Apache Flink that uses VVR 8.0.6 or later supports this parameter.

Data type mappings

Sample code

CREATE TEMPORARY TABLE sls_input(
  `time` BIGINT,
  url STRING,
  dt STRING,
  float_field FLOAT,
  double_field DOUBLE,
  boolean_field BOOLEAN,
  `__topic__` STRING METADATA VIRTUAL,
  `__source__` STRING METADATA VIRTUAL,
  `__timestamp__` STRING METADATA VIRTUAL,
   __tag__ MAP<VARCHAR, VARCHAR> METADATA VIRTUAL,
  proctime as PROCTIME()
) WITH (
  'connector' = 'sls',
  'endpoint' ='cn-hangzhou-intranet.log.aliyuncs.com',
  'accessId' = '${secret_values.ak_id}',
  'accessKey' = '${secret_values.ak_secret}',
  'starttime' = '2023-08-30 00:00:00',
  'project' ='sls-test',
  'logstore' ='sls-input'
);

CREATE TEMPORARY TABLE sls_sink(
  `time` BIGINT,
  url STRING,
  dt STRING,
  float_field FLOAT,
  double_field DOUBLE,
  boolean_field BOOLEAN,
  `__topic__` STRING,
  `__source__` STRING,
  `__timestamp__` BIGINT ,
  receive_time BIGINT
) WITH (
  'connector' = 'sls',
  'endpoint' ='cn-hangzhou-intranet.log.aliyuncs.com',
  'accessId' = '${ak_id}',
  'accessKey' = '${ak_secret}',
  'project' ='sls-test',
  'logstore' ='sls-output'
);

INSERT INTO sls_sink
SELECT 
 `time`,
  url,
  dt,
  float_field,
  double_field,
  boolean_field,
  `__topic__` ,
  `__source__` ,
  `__timestamp__` ,
  cast(__tag__['__receive_time__'] as bigint) as receive_time
FROM sls_input; 

DataStream API

public class SlsDataStreamSource {

    public static void main(String[] args) throws Exception {
        // Sets up the streaming execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // Creates and adds SLS source and sink.
        env.addSource(createSlsSource())
                .map(SlsDataStreamSource::convertMessages)
                .print();
        env.execute("SLS Stream Source");
    }

    private static SlsSourceFunction createSlsSource() {
        SLSAccessInfo accessInfo = new SLSAccessInfo();
        accessInfo.setEndpoint("yourEndpoint");
        accessInfo.setProjectName("yourProject");
        accessInfo.setLogstore("yourLogStore");
        accessInfo.setAccessId("yourAccessId");
        accessInfo.setAccessKey("yourAccessKey");

        // The batch get size must be given.
        accessInfo.setBatchGetSize(10);

        // Optional parameters
        accessInfo.setConsumerGroup("yourConsumerGroup");
        accessInfo.setMaxRetries(3);

        // time to start consuming, set to current time.
        int startInSec = (int) (new Date().getTime() / 1000);

        // time to stop consuming, -1 means never stop.
        int stopInSec = -1;

        return new SlsSourceFunction(accessInfo, startInSec, stopInSec);
    }

    private static List<String> convertMessages(SourceRecord input) {
        List<String> res = new ArrayList<>();
        for (FastLogGroup logGroup : input.getLogGroups()) {
            int logsCount = logGroup.getLogsCount();
            for (int i = 0; i < logsCount; i++) {
                FastLog log = logGroup.getLogs(i);
                int fieldCount = log.getContentsCount();
                for (int idx = 0; idx < fieldCount; idx++) {
                    FastLogContent f = log.getContents(idx);
                    res.add(String.format("key: %s, value: %s", f.getKey(), f.getValue()));
                }
            }
        }
        return res;
    }
}

public class SlsDataStreamSink {

    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.fromSequence(0, 100)
                .map((MapFunction<Long, SinkRecord>) aLong -> getSinkRecord(aLong))
                .addSink(createSlsSink())
                .name(SlsDataStreamSink.class.getSimpleName());
        env.execute("SLS Stream Sink");
    }

    private static OutputFormatSinkFunction createSlsSink() {
        Configuration conf = new Configuration();
        conf.setString(SLSOptions.ENDPOINT, "yourEndpoint");
        conf.setString(SLSOptions.PROJECT, "yourProject");
        conf.setString(SLSOptions.LOGSTORE, "yourLogStore");
        conf.setString(SLSOptions.ACCESS_ID, "yourAccessId");
        conf.setString(SLSOptions.ACCESS_KEY, "yourAccessKey");
        SLSOutputFormat outputFormat = new SLSOutputFormat(conf);
        return new OutputFormatSinkFunction<>(outputFormat);
    }

    private static SinkRecord getSinkRecord(Long seed) {
        SinkRecord record = new SinkRecord();
        LogItem logItem = new LogItem((int) (System.currentTimeMillis() / 1000));
        logItem.PushBack("level", "info");
        logItem.PushBack("name", String.valueOf(seed));
        logItem.PushBack("message", "it's a test message for " + seed.toString());
        record.setContent(logItem);
        return record;
    }

}

<dependency>
    <groupId>com.alibaba.ververica</groupId>
    <artifactId>ververica-connector-sls</artifactId>
    <version>${vvr-version}</version>
</dependency>

FAQ

What do I do if an OOM error occurs in TaskManagers and the error message "java.lang.OutOfMemoryError: Java heap space" appears for the source table when I restore a failed Flink program?