Flink-Clickhouse-Sink

Description

Flink sink for Clickhouse database. Powered by Async Http Client.

High-performance library for loading data to Clickhouse.

It has two triggers for loading data: by timeout and by buffer size.

Version map

flink	flink-clickhouse-sink
1.3.*	1.0.0

Install

Maven Central

<dependency>
  <groupId>ru.ivi.opensource</groupId>
  <artifactId>flink-clickhouse-sink</artifactId>
  <version>1.0.0</version>
</dependency>

Usage

Properties

The flink-clickhouse-sink uses two parts of configuration properties: common and for each sink in you operators chain.

The common part (use like global):

clickhouse.sink.num-writers - number of writers, which build and send requests,

clickhouse.sink.queue-max-capacity - max capacity (batches) of blank's queue,

clickhouse.sink.timeout-sec - timeout for loading data,

clickhouse.sink.retries - max number of retries,

clickhouse.sink.failed-records-path- path for failed records.

The sink part (use in chain):

clickhouse.sink.target-table - target table in Clickhouse,

clickhouse.sink.max-buffer-size- buffer size.

In code

The main thing: the clickhouse-sink works with events in string (Clickhouse insert format, like CSV) format. You have to convert your event to csv format (like usual insert in database).

For example, you have event-pojo:

class A {
   public final String str;
   public final int integer;
   
   public A(String str, int i){
       this.str = str;
       this.integer = i;
   }
}

You have to convert this pojo like this:

public static String convertToCsv(A a) {
    StringBuilder builder = new StringBuilder();
    builder.append("(");
    
    // add a.str
    builder.append("'");
    builder.append(a.str);
    builder.append("', ");
    
    // add a.intger
    builder.append(String.valueOf(a.integer));
    builder.append(" )");
    return builder.toString();
}

And then add record to sink.

You have to add global parameters for Flink environment:

StreamExecutionEnvironment environment = StreamExecutionEnvironment.createLocalEnvironment();
Map<String, String> globalParameters = new HashMap<>();

// clickhouse cluster properties
globalParameters.put(ClickhouseClusterSettings.CLICKHOUSE_HOSTS, ...);
globalParameters.put(ClickhouseClusterSettings.CLICKHOUSE_USER, ...);
globalParameters.put(ClickhouseClusterSettings.CLICKHOUSE_PASSWORD, ...);

// sink common
globalParameters.put(ClickhouseSinkConsts.TIMEOUT_SEC, ...);
globalParameters.put(ClickhouseSinkConsts.FAILED_RECORDS_PATH, ...);
globalParameters.put(ClickhouseSinkConsts.NUM_WRITERS, ...);
globalParameters.put(ClickhouseSinkConsts.NUM_RETRIES, ...);
globalParameters.put(ClickhouseSinkConsts.QUEUE_MAX_CAPACITY, ...);

// set global paramaters
ParameterTool parameters = ParameterTool.fromMap(buildGlobalParameters(config));
environment.getConfig().setGlobalJobParameters(parameters);

And add your sink like this:

// create converter
public YourEventConverter {
    String toClickHouseInsertFormat (YourEvent yourEvent){
        String chFormat = ...;
        ....
        return chFormat;
    }
}

// create props for sink
Properties props = new Properties();
props.put(ClickhouseSinkConsts.TARGET_TABLE_NAME, "your_table");
props.put(ClickhouseSinkConsts.MAX_BUFFER_SIZE, "10000");

// build chain
DataStream<YourEvent> dataStream = ...;
dataStream.map(YourEventConverter::toClickHouseInsertFormat)
          .name("convert YourEvent to Clickhouse table format")
          .addSink(new ClickhouseSink(props))
          .name("your_table clickhouse sink);

Roadmap

• maven
• reading files from "failed-records-path"
• Flink 1.7+