Flink SQL connector for ClickHouse database, this project Powered by ClickHouse JDBC.
Currently, the project supports Source/Sink Table
and Flink Catalog
.
Please create issues if you encounter bugs and any help for the project is greatly appreciated.
Option | Required | Default | Type | Description |
---|---|---|---|---|
url | required | none | String | The ClickHouse jdbc url in format clickhouse://<host>:<port> . |
username | optional | none | String | The 'username' and 'password' must both be specified if any of them is specified. |
password | optional | none | String | The ClickHouse password. |
database-name | optional | default | String | The ClickHouse database name. |
table-name | required | none | String | The ClickHouse table name. |
use-local | optional | false | Boolean | Directly read/write local tables in case of distributed table engine. |
sink.batch-size | optional | 1000 | Integer | The max flush size, over this will flush data. |
sink.flush-interval | optional | 1s | Duration | Over this flush interval mills, asynchronous threads will flush data. |
sink.max-retries | optional | 3 | Integer | The max retry times when writing records to the database failed. |
optional | false | Boolean | Removed from version 1.15, use use-local instead. |
|
sink.update-strategy | optional | update | String | Convert a record of type UPDATE_AFTER to update/insert statement or just discard it, available: update, insert, discard. |
sink.partition-strategy | optional | balanced | String | Partition strategy: balanced(round-robin), hash(partition key), shuffle(random). |
sink.partition-key | optional | none | String | Partition key used for hash strategy. |
sink.sharding.use-table-definition | optional | false | Boolean | Sharding strategy consistent with definition of distributed table, if set to true, the configuration of sink.partition-strategy and sink.partition-key will be overwritten. |
sink.ignore-delete | optional | true | Boolean | Whether to ignore delete statements. |
sink.parallelism | optional | none | Integer | Defines a custom parallelism for the sink. |
scan.partition.column | optional | none | String | The column name used for partitioning the input. |
scan.partition.num | optional | none | Integer | The number of partitions. |
scan.partition.lower-bound | optional | none | Long | The smallest value of the first partition. |
scan.partition.upper-bound | optional | none | Long | The largest value of the last partition. |
catalog.ignore-primary-key | optional | true | Boolean | Whether to ignore primary keys when using ClickHouseCatalog to create table. |
properties.* | optional | none | String | This can set and pass clickhouse-jdbc configurations. |
lookup.cache | optional | NONE | String | The caching strategy for this lookup table, including NONE and PARTIAL(not support FULL yet) |
lookup.partial-cache.expire-after-access | optional | none | Duration | Duration to expire an entry in the cache after accessing, over this time, the oldest rows will be expired. |
lookup.partial-cache.expire-after-write | optional | none | Duration | Duration to expire an entry in the cache after writing, over this time, the oldest rows will be expired. |
lookup.partial-cache.max-rows | optional | none | Long | The max number of rows of lookup cache, over this value, the oldest rows will be expired. |
lookup.partial-cache.caching-missing-key | optional | true | Boolean | Flag to cache missing key, true by default |
lookup.max-retries | optional | 3 | Integer | The max retry times if lookup database failed. |
Update/Delete Data Considerations:
use-local
to
true.breaking
Since version 1.16, we have taken shard weight into consideration, this may affect which shard the data is distributed to.
Flink Type | ClickHouse Type |
---|---|
CHAR | String |
VARCHAR | String / IP / UUID |
STRING | String / Enum |
BOOLEAN | UInt8 |
BYTES | FixedString |
DECIMAL | Decimal / Int128 / Int256 / UInt64 / UInt128 / UInt256 |
TINYINT | Int8 |
SMALLINT | Int16 / UInt8 |
INTEGER | Int32 / UInt16 / Interval |
BIGINT | Int64 / UInt32 |
FLOAT | Float32 |
DOUBLE | Float64 |
DATE | Date |
TIME | DateTime |
TIMESTAMP | DateTime |
TIMESTAMP_LTZ | DateTime |
INTERVAL_YEAR_MONTH | Int32 |
INTERVAL_DAY_TIME | Int64 |
ARRAY | Array |
MAP | Map |
ROW | Not supported |
MULTISET | Not supported |
RAW | Not supported |
The project isn't published to the maven central repository, we need to deploy/install to our own repository before use it, step as follows:
# clone the project
git clone https://github.com/itinycheng/flink-connector-clickhouse.git
# enter the project directory
cd flink-connector-clickhouse/
# display remote branches
git branch -r
# checkout the branch you need
git checkout $branch_name
# install or deploy the project to our own repository
mvn clean install -DskipTests
mvn clean deploy -DskipTests
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-clickhouse</artifactId>
<version>1.16.0-SNAPSHOT</version>
</dependency>
-- register a clickhouse table `t_user` in flink sql.
CREATE TABLE t_user (
`user_id` BIGINT,
`user_type` INTEGER,
`language` STRING,
`country` STRING,
`gender` STRING,
`score` DOUBLE,
`list` ARRAY<STRING>,
`map` Map<STRING, BIGINT>,
PRIMARY KEY (`user_id`) NOT ENFORCED
) WITH (
'connector' = 'clickhouse',
'url' = 'clickhouse://{ip}:{port}',
'database-name' = 'tutorial',
'table-name' = 'users',
'sink.batch-size' = '500',
'sink.flush-interval' = '1000',
'sink.max-retries' = '3'
);
-- read data from clickhouse
SELECT user_id, user_type from t_user;
-- write data into the clickhouse table from the table `T`
INSERT INTO t_user
SELECT cast(`user_id` as BIGINT), `user_type`, `lang`, `country`, `gender`, `score`, ARRAY['CODER', 'SPORTSMAN'], CAST(MAP['BABA', cast(10 as BIGINT), 'NIO', cast(8 as BIGINT)] AS MAP<STRING, BIGINT>) FROM T;
val tEnv = TableEnvironment.create(setting)
val props = new util.HashMap[String, String]()
props.put(ClickHouseConfig.DATABASE_NAME, "default")
props.put(ClickHouseConfig.URL, "clickhouse://127.0.0.1:8123")
props.put(ClickHouseConfig.USERNAME, "username")
props.put(ClickHouseConfig.PASSWORD, "password")
props.put(ClickHouseConfig.SINK_FLUSH_INTERVAL, "30s")
val cHcatalog = new ClickHouseCatalog("clickhouse", props)
tEnv.registerCatalog("clickhouse", cHcatalog)
tEnv.useCatalog("clickhouse")
tEnv.executeSql("insert into `clickhouse`.`default`.`t_table` select...");
TableEnvironment tEnv = TableEnvironment.create(setting);
Map<String, String> props = new HashMap<>();
props.put(ClickHouseConfig.DATABASE_NAME, "default")
props.put(ClickHouseConfig.URL, "clickhouse://127.0.0.1:8123")
props.put(ClickHouseConfig.USERNAME, "username")
props.put(ClickHouseConfig.PASSWORD, "password")
props.put(ClickHouseConfig.SINK_FLUSH_INTERVAL, "30s");
Catalog cHcatalog = new ClickHouseCatalog("clickhouse", props);
tEnv.registerCatalog("clickhouse", cHcatalog);
tEnv.useCatalog("clickhouse");
tEnv.executeSql("insert into `clickhouse`.`default`.`t_table` select...");
> CREATE CATALOG clickhouse WITH (
'type' = 'clickhouse',
'url' = 'clickhouse://127.0.0.1:8123',
'username' = 'username',
'password' = 'password',
'database-name' = 'default',
'use-local' = 'false',
...
);
> USE CATALOG clickhouse;
> SELECT user_id, user_type FROM `default`.`t_user` limit 10;
> INSERT INTO `default`.`t_user` SELECT ...;
The main branch is currently unstable and should not be used in production