Flink SQL 批模式下 ClickHouse 批量写入
内置使用
JdbcBatchingOutputFormat
批量处理类
pom依赖
<dependency>
<groupId>ru.yandex.clickhouse</groupId>
<artifactId>clickhouse-jdbc</artifactId>
<version>0.3.1-patch</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-jdbc_2.11</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>cn.hutool</groupId>
<artifactId>hutool-all</artifactId>
<version>${hutool.version}</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>${mysql.version}</version>
</dependency>
clickHouse数据源需要的扩展类:
工厂类
public class ClickHouseDynamicTableFactory implements DynamicTableSinkFactory {
public static final String IDENTIFIER = \"clickhouse\";
private static final String DRIVER_NAME = \"ru.yandex.clickhouse.ClickHouseDriver\";
public static final ConfigOption<String> URL = ConfigOptions
.key(\"url\")
.stringType()
.noDefaultValue()
.withDescription(\"the jdbc database url.\");
public static final ConfigOption<String> TABLE_NAME = ConfigOptions
.key(\"table-name\")
.stringType()
.noDefaultValue()
.withDescription(\"the jdbc table name.\");
public static final ConfigOption<String> USERNAME = ConfigOptions
.key(\"username\")
.stringType()
.noDefaultValue()
.withDescription(\"the jdbc user name.\");
public static final ConfigOption<String> PASSWORD = ConfigOptions
.key(\"password\")
.stringType()
.noDefaultValue()
.withDescription(\"the jdbc password.\");
public static final ConfigOption<String> FORMAT = ConfigOptions
.key(\"format\")
.stringType()
.noDefaultValue()
.withDescription(\"the format.\");
@Override
public String factoryIdentifier() {
return IDENTIFIER;
}
@Override
public Set<ConfigOption<?>> requiredOptions() {
Set<ConfigOption<?>> requiredOptions = new HashSet<>();
requiredOptions.add(TABLE_NAME);
requiredOptions.add(URL);
return requiredOptions;
}
@Override
public Set<ConfigOption<?>> optionalOptions() {
return new HashSet<>();
}
@Override
public DynamicTableSink createDynamicTableSink(Context context) {
// either implement your custom validation logic here ...
final FactoryUtil.TableFactoryHelper helper = FactoryUtil.createTableFactoryHelper(this, context);
final ReadableConfig config = helper.getOptions();
// validate all options
helper.validate();
// get the validated options
JdbcOptions jdbcOptions = getJdbcOptions(config);
// derive the produced data type (excluding computed columns) from the catalog table
final DataType dataType = context.getCatalogTable().getResolvedSchema().toPhysicalRowDataType();
// table sink
return new ClickHouseDynamicTableSink(jdbcOptions, dataType);
}
private JdbcOptions getJdbcOptions(ReadableConfig readableConfig) {
final String url = readableConfig.get(URL);
final JdbcOptions.Builder builder = JdbcOptions.builder()
.setDriverName(DRIVER_NAME)
.setDBUrl(url)
.setTableName(readableConfig.get(TABLE_NAME))
.setDialect(new ClickHouseDialect());
readableConfig.getOptional(USERNAME).ifPresent(builder::setUsername);
readableConfig.getOptional(PASSWORD).ifPresent(builder::setPassword);
return builder.build();
}
}
方言类
public class ClickHouseDialect implements JdbcDialect {
private static final long serialVersionUID = 1L;
@Override
public String dialectName() {
return \"ClickHouse\";
}
@Override
public boolean canHandle(String url) {
return url.startsWith(\"jdbc:clickhouse:\");
}
@Override
public JdbcRowConverter getRowConverter(RowType rowType) {
return new ClickHouseRowConverter(rowType);
}
@Override
public String getLimitClause(long l) {
return \"limit num : \" + l;
}
@Override
public Optional<String> defaultDriverName() {
return Optional.of(ClickHouseDriver.class.getName());
}
@Override
public String quoteIdentifier(String identifier) {
return \"`\" + identifier + \"`\";
}
}
Sink输出类(重点)
public class ClickHouseDynamicTableSink implements DynamicTableSink {
private final JdbcOptions jdbcOptions;
private final DataType dataType;
private static final JdbcExecutionOptions DEFAULT_EXECUTION_OPTIONS = JdbcExecutionOptions.builder()
// 写入触发数据量阈值
.withBatchSize(2000)
// 写入触发时间阈值
.withBatchIntervalMs(1000)
// 重试次数
.withMaxRetries(3)
.build();
public ClickHouseDynamicTableSink(JdbcOptions jdbcOptions, DataType dataType) {
this.jdbcOptions = jdbcOptions;
this.dataType = dataType;
}
@Override
public ChangelogMode getChangelogMode(ChangelogMode requestedMode) {
return requestedMode;
}
@SneakyThrows
@Override
public SinkRuntimeProvider getSinkRuntimeProvider(Context context) {
ClickHouseTableEnum tableEnum = ClickHouseTableEnum.valueOf(jdbcOptions.getTableName());
TableService tableService = new TableServiceImpl(dataType, tableEnum);
return SinkFunctionProvider.of(new GenericJdbcSinkFunction<>(
new JdbcBatchingOutputFormat<>(
new SimpleJdbcConnectionProvider(jdbcOptions),
DEFAULT_EXECUTION_OPTIONS,
thisContext -> JdbcBatchStatementExecutor.simple(
tableService.getInsertSql(),
tableService.getStatementBuilder(),
Function.identity()),
// 批模式下,数据对象重复利用,会发生覆盖问题,需要深拷贝对象
new RowDataConventFunction())));
}
@Override
public DynamicTableSink copy() {
return new ClickHouseDynamicTableSink(jdbcOptions, dataType);
}
@Override
public String asSummaryString() {
return \"ClickHouse Table Sink\";
}
@Slf4j
static class RowDataConventFunction implements JdbcBatchingOutputFormat.RecordExtractor<RowData, RowData>, Serializable {
@Override
public RowData apply(RowData rowData) {
BoxedWrapperRowData newRowData = null;
try {
newRowData = new BoxedWrapperRowData(rowData.getArity());
// 利用反射拷贝旧对象的值
Field field = ReflectUtil.getField(BoxedWrapperRowData.class, \"fields\");
Object[] fields = (Object[]) ReflectUtil.getFieldValue(rowData, field);
Object[] newFields = new Object[fields.length];
for (int i = 0; i < fields.length; i++) {
newFields[i] = Objects.isNull(fields[i]) ? null : ReflectUtil.invoke(fields[i], \"copy\");
}
ReflectUtil.setFieldValue(newRowData, \"fields\", newFields);
} catch (Exception e) {
log.error(\"convert error,data:{},\", rowData, e);
}
return newRowData;
}
}
}
转换类
public class ClickHouseRowConverter extends AbstractJdbcRowConverter {
private static final long serialVersionUID = 1L;
public ClickHouseRowConverter(RowType rowType) {
super(rowType);
}
@Override
public String converterName() {
return \"ClickHouse\";
}
}
支持序列化的BiFunction
@FunctionalInterface
public interface MyBiFunction<T, U, R> extends Serializable {
R apply(T t, U u);
}
sql 生成类
public class TableServiceImpl {
private final List<LogicalType> logicalTypeList;
private final String insertSql;
public TableServiceImpl(DataType dataType, ClickHouseTableEnum tableEnum) {
this.logicalTypeList = dataType.getLogicalType().getChildren();
this.insertSql = initInsertSql(tableEnum);
}
private static final Map<Class<? extends LogicalType>, MyBiFunction<RowData, Integer, Object>> FUNCTION_MAP = Maps.newHashMap();
static {
// 我的业务中用到的类型,可根据自己的业务,进行增加
FUNCTION_MAP.put(IntType.class, RowData::getInt);
FUNCTION_MAP.put(VarCharType.class, RowData::getString);
FUNCTION_MAP.put(DoubleType.class, RowData::getDouble);
FUNCTION_MAP.put(BigIntType.class, RowData::getLong);
FUNCTION_MAP.put(CharType.class, RowData::getString);
}
public String getInsertSql() {
return insertSql;
}
public JdbcStatementBuilder<RowData> getStatementBuilder() {
return (statement, value) -> {
for (int i = 0; i < logicalTypeList.size(); i++) {
LogicalType logicalType = logicalTypeList.get(i);
Object realValue = FUNCTION_MAP.get(logicalType.getClass()).apply(value, i);
statement.setObject(i + 1, realValue);
}
};
}
// 根据枚举字段配置,生成 insert sql
public static String initInsertSql(ClickHouseTableEnum tableEnum) {
List<String> columns = tableEnum.getColumns().stream().map(ClickHouseTableEnum.ColumnObj::getColumnName).collect(Collectors.toList());
return String.format(\"insert into %s (%s) values (%s)\"
, tableEnum.name()
, StrUtil.join(\",\", columns)
, StrUtil.repeatAndJoin(\"?\", columns.size(), \",\"));
}
public static void main(String[] args) {
System.out.println(initInsertSql(ClickHouseTableEnum.attr_order_group));
}
}
clickHouseTable 枚举类
@Getter
public enum ClickHouseTableEnum {
/**
* 测试表,因为业务需要,我定义的 ColumnObj 类,实际用个字符串就ok
*/
test(Lists.newArrayList(
ColumnObj.of(\"name\")
, ColumnObj.of(\"age\")
)),
;
private final List<ColumnObj> columns;
ClickHouseTableEnum(List<ColumnObj> columns) {
this.columns = columns;
}
@Getter
@Setter
@ToString
public static class ColumnObj {
/**
* clickHouse 中字段名称
*/
private String columnName;
/**
* flink sql 中获取字段的key
*/
private String sqlColumnKey;
/**
* 两个值相同的情况,使用此构造函数
*/
private ColumnObj(String columnName) {
this.columnName = columnName;
this.sqlColumnKey = columnName;
}
}
}
Spi 配置自定义的工厂
resources
目录下,创建META-INF/services
目录创建文件:
org.apache.flink.table.factories.Factory
内容如下:指向自己的工厂类全路径
com.xxx.xxx.xxx.ClickHouseDynamicTableFactory
输出测试
public class Test {
public static void main(String[] args) {
// 初始化 批模式环境
EnvironmentSettings settings = EnvironmentSettings.newInstance().inBatchMode().build();
Configuration configuration = settings.toConfiguration();
configuration.set(CoreOptions.DEFAULT_PARALLELISM, 5);
TableEnvironment tableEnv = TableEnvironment.create(configuration);
// 创建 clickHouse 输出表
// 注意,WITH 后面的参数,table-name 需要跟 clickHouseTable 枚举类中对应上
tableEnv.executeSql(\"CREATE TABLE out_table_test (\\n\" +
\" `name` STRING,\\n\" +
\" `age` INT\\n\" +
\") WITH (\\n\" +
\" \'connector\' = \'clickhouse\',\\n\" +
\" \'url\' = \'jdbc:clickhouse://172.23.4.32:8123/test\',\\n\" +
\" \'table-name\' = \'test\'\\n\" +
\")\");
Table table = tableEnv.sqlQuery(\"select \'alice\',18 \");
table.executeInsert(\"out_table_test\");
// 打印日志
printLog(tableEnv, table, \"test\");
}
private static void printLog(TableEnvironment tableEnv, Table endTable, String outTableName) {
String outPrint = \"consolePrint_\" + outTableName;
tableEnv.executeSql(\"CREATE TABLE \" + outPrint + \" \" + endTable.getResolvedSchema() + \" WITH (\\n\" +
\" \'connector\' = \'print\'\\n\" +
\")\");
endTable.executeInsert(outPrint);
Table countTable = tableEnv.sqlQuery(\"select count(*) from \" + endTable);
tableEnv.executeSql(\"CREATE TABLE \" + outPrint + \"_count \" + countTable.getResolvedSchema() + \" WITH (\\n\" +
\" \'connector\' = \'print\'\\n\" +
\")\");
countTable.executeInsert(outPrint + \"_count\");
}
}
来源:https://www.cnblogs.com/lalala1/p/16692511.html
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