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Version: 2.0.0

Kafka Example

Here we use an example to introduce how to use Apache InLong creating MySQL -> Kafka -> ClickHouse data ingestion.

Deployment​

Install InLong​

Before we begin, we need to install InLong. Here we provide two ways:

Install ClickHouse​

docker run -d --rm --net=host --name clickhouse -e CLICKHOUSE_USER=admin -e CLICKHOUSE_PASSWORD=inlong -e CLICKHOUSE_DEFAULT_ACCESS_MANAGEMENT=1 clickhouse/clickhouse-server:22.8

Install Kafka​

# Prepare zookeeper for Kafka
docker run -d --name zookeeper -p 2181:2181 -t wurstmeister/zookeeper
# Install Kafka 
docker run -d --name kafka -p 9092:9092 -e KAFKA_BROKER_ID=0 -e KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 --link zookeeper -e KAFKA_ADVERTISED_LISTENERS=PLAINTEXT://kafka:9092 -e KAFKA_LISTENERS=PLAINTEXT://0.0.0.0:9092 -t wurstmeister/kafka

Cluster Initialize​

When all containers are successfully started, you can access the InLong dashboard address http://localhost, and use the following default account to log in.

User: admin
Password: inlong

Create Cluster Tag​

Click [Clusters] -> [ClusterTags] -> [Create] on the page to specify the cluster label name and person in charge. Create Cluster label

caution

Since each component reports the ClusterTags as default_cluster by default, do not use other names.

Register Kafka Cluster​

Click [Clusters] -> [Create] on the page to register Kafka Cluster. Create kafka cluster

Register Clickhouse DataNodes​

Click [DataNodes] -> [Create] on the page to register ClickHouse DataNodes. Create kafka cluster

Create Task​

Create Data Streams Group​

Click [Ingestion] -> [Create], input ID and select Kafka MQ Type. Create datastream

Create Data Stream​

Click [Next] -> [Create], config data stream. Create datastream

Create Data Source​

Click [Sources create] -> [MySQL], config data source information. Create datastream

note

Please create test_mysql_db.test_mysql_table database and table, it's schema is: CREATE TABLE test_mysql_db.test_mysql_table ( id INT PRIMARY KEY, name VARCHAR(50) );

Create Data Sink​

Click [Sinks create] -> [ClickHouse], input Name, DbName, TableName and select created ck DataNode and so on, then click [save]. Create data object

Approve Data Stream​

Click [Approval] -> [MyApproval] -> [Detail] -> [Select Cluster tag] -> [Ok]. clickhouse

Back to [Ingestion] page, wait for [configuration success]. clickhouse

Test Data​

Send Data​

clickhouse Add 1000 data items to MySQL.

Verify Data​

Check data in [Audit] page. clickhouse

then enter ClickHouse container, check data in table. clickhouse

Questions​

Task Configuration Failed​

Generally, the MQ or Flink group configuration is incorrect. You can view the error information on the page, or enter the Manager container to view detailed logs.

The script for sending data​

#!/bin/bash

# MySQL information
DB_HOST="mysql"
DB_USER="root"
DB_PASS="inlong"
DB_NAME="test_mysql_db"
DB_TABLE="test_mysql_table"

# insert data by a loop
for ((i=1; i<=1000; i++))
do
    # generate data
    id=$i
    name="name_$i"
    # insert data
    query="INSERT INTO $DB_TABLE (id, name) VALUES ($id, '$name');"
    # execute insert
    mysql -h $DB_HOST -u $DB_USER -p$DB_PASS $DB_NAME -e "$query"
done