Flik SQL 自定义SQL SELECT并行度
FlinkHintStrategies 增加 hint task（完整代码）/** Licensed to the Apache Software Foundation (ASF) under one* or more contributor license agreements.See the NOTICE file* distributed with this work for additio
·
FlinkHintStrategies 增加 hint task（完整代码）
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.flink.table.planner.hint;
import org.apache.calcite.rel.hint.HintPredicates;
import org.apache.calcite.rel.hint.HintStrategy;
import org.apache.calcite.rel.hint.HintStrategyTable;
import org.apache.calcite.util.Litmus;
/** A collection of Flink style {@link HintStrategy}s. */
public abstract class FlinkHintStrategies {
/**
* Customize the {@link HintStrategyTable} which contains hint strategies supported by Flink.
*/
public static HintStrategyTable createHintStrategyTable() {
return HintStrategyTable.builder()
// Configure to always throw when we encounter any hint errors
// (either the non-registered hint or the hint format).
.errorHandler(Litmus.THROW)
.hintStrategy(
FlinkHints.HINT_NAME_OPTIONS,
HintStrategy.builder(HintPredicates.TABLE_SCAN)
.optionChecker(
(hint, errorHandler) ->
errorHandler.check(
hint.kvOptions.size() > 0,
"Hint [{}] only support non empty key value options",
hint.hintName))
.build())
.hintStrategy(
"task", //增加 HINT task(int) 并行参数标识
HintStrategy.builder(HintPredicates.SET_VAR)
/*.optionChecker(
(hint, errorHandler) ->
errorHandler.check(
hint.kvOptions.size() > 0,
"Hint [{}] only support non empty key value task",
hint.hintName))*/
.build())
.build();
}
}
2：PlannerBase 读取配置并启用task(int)
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.flink.table.planner.delegation
import org.apache.flink.annotation.VisibleForTesting
import org.apache.flink.api.dag.Transformation
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment
import org.apache.flink.table.api.config.ExecutionConfigOptions
import org.apache.flink.table.api.{TableConfig, TableEnvironment, TableException, TableSchema}
import org.apache.flink.table.catalog._
import org.apache.flink.table.connector.sink.DynamicTableSink
import org.apache.flink.table.delegation.{Executor, Parser, Planner}
import org.apache.flink.table.descriptors.{ConnectorDescriptorValidator, DescriptorProperties}
import org.apache.flink.table.factories.{FactoryUtil, TableFactoryUtil}
import org.apache.flink.table.operations.OutputConversionModifyOperation.UpdateMode
import org.apache.flink.table.operations._
import org.apache.flink.table.planner.JMap
import org.apache.flink.table.planner.calcite._
import org.apache.flink.table.planner.catalog.CatalogManagerCalciteSchema
import org.apache.flink.table.planner.expressions.PlannerTypeInferenceUtilImpl
import org.apache.flink.table.planner.hint.FlinkHints
import org.apache.flink.table.planner.plan.nodes.calcite.LogicalLegacySink
import org.apache.flink.table.planner.plan.nodes.exec.ExecNode
import org.apache.flink.table.planner.plan.nodes.physical.FlinkPhysicalRel
import org.apache.flink.table.planner.plan.optimize.Optimizer
import org.apache.flink.table.planner.plan.reuse.SubplanReuser
import org.apache.flink.table.planner.plan.utils.SameRelObjectShuttle
import org.apache.flink.table.planner.sinks.DynamicSinkUtils.validateSchemaAndApplyImplicitCast
import org.apache.flink.table.planner.sinks.TableSinkUtils.{inferSinkPhysicalSchema, validateLogicalPhysicalTypesCompatible, validateTableSink}
import org.apache.flink.table.planner.sinks.{DataStreamTableSink, DynamicSinkUtils, SelectTableSinkBase, SelectTableSinkSchemaConverter}
import org.apache.flink.table.planner.utils.{JavaScalaConversionUtil, PlanUtil}
import org.apache.flink.table.sinks.TableSink
import org.apache.flink.table.types.utils.LegacyTypeInfoDataTypeConverter
import org.apache.flink.table.utils.TableSchemaUtils
import org.apache.calcite.jdbc.CalciteSchemaBuilder.asRootSchema
import org.apache.calcite.plan.{RelTrait, RelTraitDef}
import org.apache.calcite.rel.RelNode
import org.apache.calcite.rel.`type`.RelDataType
import org.apache.calcite.tools.FrameworkConfig
import java.util
import java.util.function.{Function => JFunction, Supplier => JSupplier}
import _root_.scala.collection.JavaConversions._
/**
* Implementation of [[Planner]] for blink planner. It supports only streaming use cases.
* (The new [[org.apache.flink.table.sources.InputFormatTableSource]] should work, but will be
* handled as streaming sources, and no batch specific optimizations will be applied).
*
* @param executor instance of [[Executor]], needed to extract
* [[StreamExecutionEnvironment]] for
* [[org.apache.flink.table.sources.StreamTableSource.getDataStream]]
* @param config mutable configuration passed from corresponding [[TableEnvironment]]
* @param functionCatalog catalog of functions
* @param catalogManager manager of catalog meta objects such as tables, views, databases etc.
* @param isStreamingMode Determines if the planner should work in a batch (false}) or
* streaming (true) mode.
*/
abstract class PlannerBase(
executor: Executor,
config: TableConfig,
val functionCatalog: FunctionCatalog,
val catalogManager: CatalogManager,
isStreamingMode: Boolean)
extends Planner {
// temporary utility until we don't use planner expressions anymore
functionCatalog.setPlannerTypeInferenceUtil(PlannerTypeInferenceUtilImpl.INSTANCE)
private val sqlExprToRexConverterFactory = new SqlExprToRexConverterFactory {
override def create(tableRowType: RelDataType): SqlExprToRexConverter =
plannerContext.createSqlExprToRexConverter(tableRowType)
}
private val parser: Parser = new ParserImpl(
catalogManager,
new JSupplier[FlinkPlannerImpl] {
override def get(): FlinkPlannerImpl = createFlinkPlanner
},
// we do not cache the parser in order to use the most up to
// date configuration. Users might change parser configuration in TableConfig in between
// parsing statements
new JSupplier[CalciteParser] {
override def get(): CalciteParser = plannerContext.createCalciteParser()
},
new JFunction[TableSchema, SqlExprToRexConverter] {
override def apply(t: TableSchema): SqlExprToRexConverter = {
sqlExprToRexConverterFactory.create(plannerContext.getTypeFactory.buildRelNodeRowType(t))
}
}
)
@VisibleForTesting
private[flink] val plannerContext: PlannerContext =
new PlannerContext(
config,
functionCatalog,
catalogManager,
asRootSchema(new CatalogManagerCalciteSchema(catalogManager, isStreamingMode)),
getTraitDefs.toList
)
/** Returns the [[FlinkRelBuilder]] of this TableEnvironment. */
private[flink] def getRelBuilder: FlinkRelBuilder = {
val currentCatalogName = catalogManager.getCurrentCatalog
val currentDatabase = catalogManager.getCurrentDatabase
plannerContext.createRelBuilder(currentCatalogName, currentDatabase)
}
/** Returns the Calcite [[FrameworkConfig]] of this TableEnvironment. */
@VisibleForTesting
private[flink] def createFlinkPlanner: FlinkPlannerImpl = {
val currentCatalogName = catalogManager.getCurrentCatalog
val currentDatabase = catalogManager.getCurrentDatabase
plannerContext.createFlinkPlanner(currentCatalogName, currentDatabase)
}
/** Returns the [[FlinkTypeFactory]] of this TableEnvironment. */
private[flink] def getTypeFactory: FlinkTypeFactory = plannerContext.getTypeFactory
/** Returns specific RelTraitDefs depends on the concrete type of this TableEnvironment. */
protected def getTraitDefs: Array[RelTraitDef[_ <: RelTrait]]
/** Returns specific query [[Optimizer]] depends on the concrete type of this TableEnvironment. */
protected def getOptimizer: Optimizer
def getTableConfig: TableConfig = config
private[flink] def getExecEnv: StreamExecutionEnvironment = {
executor.asInstanceOf[ExecutorBase].getExecutionEnvironment
}
override def getParser: Parser = parser
override def translate(
modifyOperations: util.List[ModifyOperation]): util.List[Transformation[_]] = {
if (modifyOperations.isEmpty) {
return List.empty[Transformation[_]]
}
// prepare the execEnv before translating
getExecEnv.configure(
getTableConfig.getConfiguration,
Thread.currentThread().getContextClassLoader)
overrideEnvParallelism()
val relNodes = modifyOperations.map(translateToRel)
val optimizedRelNodes = optimize(relNodes)
val execNodes = translateToExecNodePlan(optimizedRelNodes)
val transformation = translateToPlan(execNodes)
//****************读取配置，设置SQL查询的并行度 PlanUtil.overrideTransformationParallelism(PlanUtil.getHintValue(modifyOperations,"task"), transformation)
}
protected def overrideEnvParallelism(): Unit = {
// Use config parallelism to override env parallelism.
val defaultParallelism = getTableConfig.getConfiguration.getInteger(
ExecutionConfigOptions.TABLE_EXEC_RESOURCE_DEFAULT_PARALLELISM)
if (defaultParallelism > 0) {
getExecEnv.getConfig.setParallelism(defaultParallelism)
}
}
override def getCompletionHints(statement: String, position: Int): Array[String] = {
val planner = createFlinkPlanner
planner.getCompletionHints(statement, position)
}
/**
* Converts a relational tree of [[ModifyOperation]] into a Calcite relational expression.
*/
@VisibleForTesting
private[flink] def translateToRel(modifyOperation: ModifyOperation): RelNode = {
modifyOperation match {
case s: UnregisteredSinkModifyOperation[_] =>
val input = getRelBuilder.queryOperation(s.getChild).build()
val sinkSchema = s.getSink.getTableSchema
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(input, sinkSchema, null, getTypeFactory)
LogicalLegacySink.create(
query,
s.getSink,
"UnregisteredSink",
ConnectorCatalogTable.sink(s.getSink, !isStreamingMode))
case s: SelectSinkOperation =>
val input = getRelBuilder.queryOperation(s.getChild).build()
// convert query schema to sink schema
val sinkSchema = SelectTableSinkSchemaConverter.convertTimeAttributeToRegularTimestamp(
SelectTableSinkSchemaConverter.changeDefaultConversionClass(s.getChild.getTableSchema))
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(input, sinkSchema, null, getTypeFactory)
val sink = createSelectTableSink(sinkSchema)
s.setSelectResultProvider(sink.getSelectResultProvider)
LogicalLegacySink.create(
query,
sink,
"collect",
ConnectorCatalogTable.sink(sink, !isStreamingMode))
case catalogSink: CatalogSinkModifyOperation =>
val input = getRelBuilder.queryOperation(modifyOperation.getChild).build()
val identifier = catalogSink.getTableIdentifier
val dynamicOptions = catalogSink.getDynamicOptions
getTableSink(identifier, dynamicOptions).map {
case (table, sink: TableSink[_]) =>
// check the logical field type and physical field type are compatible
val queryLogicalType = FlinkTypeFactory.toLogicalRowType(input.getRowType)
// validate logical schema and physical schema are compatible
validateLogicalPhysicalTypesCompatible(table, sink, queryLogicalType)
// validate TableSink
validateTableSink(catalogSink, identifier, sink, table.getPartitionKeys)
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(
input,
TableSchemaUtils.getPhysicalSchema(table.getSchema),
catalogSink.getTableIdentifier,
getTypeFactory)
LogicalLegacySink.create(
query,
sink,
identifier.toString,
table,
catalogSink.getStaticPartitions.toMap)
case (table, sink: DynamicTableSink) =>
DynamicSinkUtils.toRel(getRelBuilder, input, catalogSink, sink, table)
} match {
case Some(sinkRel) => sinkRel
case None =>
throw new TableException(s"Sink ${catalogSink.getTableIdentifier} does not exists")
}
case outputConversion: OutputConversionModifyOperation =>
val input = getRelBuilder.queryOperation(outputConversion.getChild).build()
val (needUpdateBefore, withChangeFlag) = outputConversion.getUpdateMode match {
case UpdateMode.RETRACT => (true, true)
case UpdateMode.APPEND => (false, false)
case UpdateMode.UPSERT => (false, true)
}
val typeInfo = LegacyTypeInfoDataTypeConverter.toLegacyTypeInfo(outputConversion.getType)
val inputLogicalType = FlinkTypeFactory.toLogicalRowType(input.getRowType)
val sinkPhysicalSchema = inferSinkPhysicalSchema(
outputConversion.getType,
inputLogicalType,
withChangeFlag)
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(
input,
sinkPhysicalSchema,
null,
getTypeFactory)
val tableSink = new DataStreamTableSink(
FlinkTypeFactory.toTableSchema(query.getRowType),
typeInfo,
needUpdateBefore,
withChangeFlag)
LogicalLegacySink.create(
query,
tableSink,
"DataStreamTableSink",
ConnectorCatalogTable.sink(tableSink, !isStreamingMode))
case _ =>
throw new TableException(s"Unsupported ModifyOperation: $modifyOperation")
}
}
@VisibleForTesting
private[flink] def optimize(relNodes: Seq[RelNode]): Seq[RelNode] = {
val optimizedRelNodes = getOptimizer.optimize(relNodes)
require(optimizedRelNodes.size == relNodes.size)
optimizedRelNodes
}
@VisibleForTesting
private[flink] def optimize(relNode: RelNode): RelNode = {
val optimizedRelNodes = getOptimizer.optimize(Seq(relNode))
require(optimizedRelNodes.size == 1)
optimizedRelNodes.head
}
/**
* Converts [[FlinkPhysicalRel]] DAG to [[ExecNode]] DAG, and tries to reuse duplicate sub-plans.
*/
@VisibleForTesting
private[flink] def translateToExecNodePlan(
optimizedRelNodes: Seq[RelNode]): util.List[ExecNode[_, _]] = {
require(optimizedRelNodes.forall(_.isInstanceOf[FlinkPhysicalRel]))
// Rewrite same rel object to different rel objects
// in order to get the correct dag (dag reuse is based on object not digest)
val shuttle = new SameRelObjectShuttle()
val relsWithoutSameObj = optimizedRelNodes.map(_.accept(shuttle))
// reuse subplan
val reusedPlan = SubplanReuser.reuseDuplicatedSubplan(relsWithoutSameObj, config)
// convert FlinkPhysicalRel DAG to ExecNode DAG
reusedPlan.map(_.asInstanceOf[ExecNode[_, _]])
}
/**
* Translates a [[ExecNode]] DAG into a [[Transformation]] DAG.
*
* @param execNodes The node DAG to translate.
* @return The [[Transformation]] DAG that corresponds to the node DAG.
*/
protected def translateToPlan(execNodes: util.List[ExecNode[_, _]]): util.List[Transformation[_]]
/**
* Creates a [[SelectTableSinkBase]] for a select query.
*
* @param tableSchema the table schema of select result.
* @return The sink to fetch the select result.
*/
protected def createSelectTableSink(tableSchema: TableSchema): SelectTableSinkBase[_]
private def getTableSink(
objectIdentifier: ObjectIdentifier,
dynamicOptions: JMap[String, String])
: Option[(CatalogTable, Any)] = {
val lookupResult = JavaScalaConversionUtil.toScala(catalogManager.getTable(objectIdentifier))
lookupResult
.map(_.getTable) match {
case Some(table: ConnectorCatalogTable[_, _]) =>
JavaScalaConversionUtil.toScala(table.getTableSink) match {
case Some(sink) => Some(table, sink)
case None => None
}
case Some(table: CatalogTable) =>
val catalog = catalogManager.getCatalog(objectIdentifier.getCatalogName)
val tableToFind = if (dynamicOptions.nonEmpty) {
table.copy(FlinkHints.mergeTableOptions(dynamicOptions, table.getProperties))
} else {
table
}
val isTemporary = lookupResult.get.isTemporary
if (isLegacyConnectorOptions(objectIdentifier, table, isTemporary)) {
val tableSink = TableFactoryUtil.findAndCreateTableSink(
catalog.orElse(null),
objectIdentifier,
tableToFind,
getTableConfig.getConfiguration,
isStreamingMode,
isTemporary)
Option(table, tableSink)
} else {
val tableSink = FactoryUtil.createTableSink(
catalog.orElse(null),
objectIdentifier,
tableToFind,
getTableConfig.getConfiguration,
Thread.currentThread().getContextClassLoader,
isTemporary)
Option(table, tableSink)
}
case _ => None
}
}
/**
* Checks whether the [[CatalogTable]] uses legacy connector sink options.
*/
private def isLegacyConnectorOptions(
objectIdentifier: ObjectIdentifier,
catalogTable: CatalogTable,
isTemporary: Boolean) = {
// normalize option keys
val properties = new DescriptorProperties(true)
properties.putProperties(catalogTable.getOptions)
if (properties.containsKey(ConnectorDescriptorValidator.CONNECTOR_TYPE)) {
true
} else {
val catalog = catalogManager.getCatalog(objectIdentifier.getCatalogName)
try {
// try to create legacy table source using the options,
// some legacy factories uses the new 'connector' key
TableFactoryUtil.findAndCreateTableSink(
catalog.orElse(null),
objectIdentifier,
catalogTable,
getTableConfig.getConfiguration,
isStreamingMode,
isTemporary)
// success, then we will use the legacy factories
true
} catch {
// fail, then we will use new factories
case _: Throwable => false
}
}
}
}
P
lanUtil 解析task(int) 参数工具类
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.flink.table.planner.delegation
import org.apache.flink.annotation.VisibleForTesting
import org.apache.flink.api.dag.Transformation
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment
import org.apache.flink.table.api.config.ExecutionConfigOptions
import org.apache.flink.table.api.{TableConfig, TableEnvironment, TableException, TableSchema}
import org.apache.flink.table.catalog._
import org.apache.flink.table.connector.sink.DynamicTableSink
import org.apache.flink.table.delegation.{Executor, Parser, Planner}
import org.apache.flink.table.descriptors.{ConnectorDescriptorValidator, DescriptorProperties}
import org.apache.flink.table.factories.{FactoryUtil, TableFactoryUtil}
import org.apache.flink.table.operations.OutputConversionModifyOperation.UpdateMode
import org.apache.flink.table.operations._
import org.apache.flink.table.planner.JMap
import org.apache.flink.table.planner.calcite._
import org.apache.flink.table.planner.catalog.CatalogManagerCalciteSchema
import org.apache.flink.table.planner.expressions.PlannerTypeInferenceUtilImpl
import org.apache.flink.table.planner.hint.FlinkHints
import org.apache.flink.table.planner.plan.nodes.calcite.LogicalLegacySink
import org.apache.flink.table.planner.plan.nodes.exec.ExecNode
import org.apache.flink.table.planner.plan.nodes.physical.FlinkPhysicalRel
import org.apache.flink.table.planner.plan.optimize.Optimizer
import org.apache.flink.table.planner.plan.reuse.SubplanReuser
import org.apache.flink.table.planner.plan.utils.SameRelObjectShuttle
import org.apache.flink.table.planner.sinks.DynamicSinkUtils.validateSchemaAndApplyImplicitCast
import org.apache.flink.table.planner.sinks.TableSinkUtils.{inferSinkPhysicalSchema, validateLogicalPhysicalTypesCompatible, validateTableSink}
import org.apache.flink.table.planner.sinks.{DataStreamTableSink, DynamicSinkUtils, SelectTableSinkBase, SelectTableSinkSchemaConverter}
import org.apache.flink.table.planner.utils.{JavaScalaConversionUtil, PlanUtil}
import org.apache.flink.table.sinks.TableSink
import org.apache.flink.table.types.utils.LegacyTypeInfoDataTypeConverter
import org.apache.flink.table.utils.TableSchemaUtils
import org.apache.calcite.jdbc.CalciteSchemaBuilder.asRootSchema
import org.apache.calcite.plan.{RelTrait, RelTraitDef}
import org.apache.calcite.rel.RelNode
import org.apache.calcite.rel.`type`.RelDataType
import org.apache.calcite.tools.FrameworkConfig
import java.util
import java.util.function.{Function => JFunction, Supplier => JSupplier}
import _root_.scala.collection.JavaConversions._
/**
* Implementation of [[Planner]] for blink planner. It supports only streaming use cases.
* (The new [[org.apache.flink.table.sources.InputFormatTableSource]] should work, but will be
* handled as streaming sources, and no batch specific optimizations will be applied).
*
* @param executor instance of [[Executor]], needed to extract
* [[StreamExecutionEnvironment]] for
* [[org.apache.flink.table.sources.StreamTableSource.getDataStream]]
* @param config mutable configuration passed from corresponding [[TableEnvironment]]
* @param functionCatalog catalog of functions
* @param catalogManager manager of catalog meta objects such as tables, views, databases etc.
* @param isStreamingMode Determines if the planner should work in a batch (false}) or
* streaming (true) mode.
*/
abstract class PlannerBase(
executor: Executor,
config: TableConfig,
val functionCatalog: FunctionCatalog,
val catalogManager: CatalogManager,
isStreamingMode: Boolean)
extends Planner {
// temporary utility until we don't use planner expressions anymore
functionCatalog.setPlannerTypeInferenceUtil(PlannerTypeInferenceUtilImpl.INSTANCE)
private val sqlExprToRexConverterFactory = new SqlExprToRexConverterFactory {
override def create(tableRowType: RelDataType): SqlExprToRexConverter =
plannerContext.createSqlExprToRexConverter(tableRowType)
}
private val parser: Parser = new ParserImpl(
catalogManager,
new JSupplier[FlinkPlannerImpl] {
override def get(): FlinkPlannerImpl = createFlinkPlanner
},
// we do not cache the parser in order to use the most up to
// date configuration. Users might change parser configuration in TableConfig in between
// parsing statements
new JSupplier[CalciteParser] {
override def get(): CalciteParser = plannerContext.createCalciteParser()
},
new JFunction[TableSchema, SqlExprToRexConverter] {
override def apply(t: TableSchema): SqlExprToRexConverter = {
sqlExprToRexConverterFactory.create(plannerContext.getTypeFactory.buildRelNodeRowType(t))
}
}
)
@VisibleForTesting
private[flink] val plannerContext: PlannerContext =
new PlannerContext(
config,
functionCatalog,
catalogManager,
asRootSchema(new CatalogManagerCalciteSchema(catalogManager, isStreamingMode)),
getTraitDefs.toList
)
/** Returns the [[FlinkRelBuilder]] of this TableEnvironment. */
private[flink] def getRelBuilder: FlinkRelBuilder = {
val currentCatalogName = catalogManager.getCurrentCatalog
val currentDatabase = catalogManager.getCurrentDatabase
plannerContext.createRelBuilder(currentCatalogName, currentDatabase)
}
/** Returns the Calcite [[FrameworkConfig]] of this TableEnvironment. */
@VisibleForTesting
private[flink] def createFlinkPlanner: FlinkPlannerImpl = {
val currentCatalogName = catalogManager.getCurrentCatalog
val currentDatabase = catalogManager.getCurrentDatabase
plannerContext.createFlinkPlanner(currentCatalogName, currentDatabase)
}
/** Returns the [[FlinkTypeFactory]] of this TableEnvironment. */
private[flink] def getTypeFactory: FlinkTypeFactory = plannerContext.getTypeFactory
/** Returns specific RelTraitDefs depends on the concrete type of this TableEnvironment. */
protected def getTraitDefs: Array[RelTraitDef[_ <: RelTrait]]
/** Returns specific query [[Optimizer]] depends on the concrete type of this TableEnvironment. */
protected def getOptimizer: Optimizer
def getTableConfig: TableConfig = config
private[flink] def getExecEnv: StreamExecutionEnvironment = {
executor.asInstanceOf[ExecutorBase].getExecutionEnvironment
}
override def getParser: Parser = parser
override def translate(
modifyOperations: util.List[ModifyOperation]): util.List[Transformation[_]] = {
if (modifyOperations.isEmpty) {
return List.empty[Transformation[_]]
}
// prepare the execEnv before translating
getExecEnv.configure(
getTableConfig.getConfiguration,
Thread.currentThread().getContextClassLoader)
overrideEnvParallelism()
val relNodes = modifyOperations.map(translateToRel)
val optimizedRelNodes = optimize(relNodes)
val execNodes = translateToExecNodePlan(optimizedRelNodes)
val transformation = translateToPlan(execNodes)
PlanUtil.overrideTransformationParallelism(PlanUtil.getHintValue(modifyOperations,"task"), transformation)
}
protected def overrideEnvParallelism(): Unit = {
// Use config parallelism to override env parallelism.
val defaultParallelism = getTableConfig.getConfiguration.getInteger(
ExecutionConfigOptions.TABLE_EXEC_RESOURCE_DEFAULT_PARALLELISM)
if (defaultParallelism > 0) {
getExecEnv.getConfig.setParallelism(defaultParallelism)
}
}
override def getCompletionHints(statement: String, position: Int): Array[String] = {
val planner = createFlinkPlanner
planner.getCompletionHints(statement, position)
}
/**
* Converts a relational tree of [[ModifyOperation]] into a Calcite relational expression.
*/
@VisibleForTesting
private[flink] def translateToRel(modifyOperation: ModifyOperation): RelNode = {
modifyOperation match {
case s: UnregisteredSinkModifyOperation[_] =>
val input = getRelBuilder.queryOperation(s.getChild).build()
val sinkSchema = s.getSink.getTableSchema
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(input, sinkSchema, null, getTypeFactory)
LogicalLegacySink.create(
query,
s.getSink,
"UnregisteredSink",
ConnectorCatalogTable.sink(s.getSink, !isStreamingMode))
case s: SelectSinkOperation =>
val input = getRelBuilder.queryOperation(s.getChild).build()
// convert query schema to sink schema
val sinkSchema = SelectTableSinkSchemaConverter.convertTimeAttributeToRegularTimestamp(
SelectTableSinkSchemaConverter.changeDefaultConversionClass(s.getChild.getTableSchema))
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(input, sinkSchema, null, getTypeFactory)
val sink = createSelectTableSink(sinkSchema)
s.setSelectResultProvider(sink.getSelectResultProvider)
LogicalLegacySink.create(
query,
sink,
"collect",
ConnectorCatalogTable.sink(sink, !isStreamingMode))
case catalogSink: CatalogSinkModifyOperation =>
val input = getRelBuilder.queryOperation(modifyOperation.getChild).build()
val identifier = catalogSink.getTableIdentifier
val dynamicOptions = catalogSink.getDynamicOptions
getTableSink(identifier, dynamicOptions).map {
case (table, sink: TableSink[_]) =>
// check the logical field type and physical field type are compatible
val queryLogicalType = FlinkTypeFactory.toLogicalRowType(input.getRowType)
// validate logical schema and physical schema are compatible
validateLogicalPhysicalTypesCompatible(table, sink, queryLogicalType)
// validate TableSink
validateTableSink(catalogSink, identifier, sink, table.getPartitionKeys)
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(
input,
TableSchemaUtils.getPhysicalSchema(table.getSchema),
catalogSink.getTableIdentifier,
getTypeFactory)
LogicalLegacySink.create(
query,
sink,
identifier.toString,
table,
catalogSink.getStaticPartitions.toMap)
case (table, sink: DynamicTableSink) =>
DynamicSinkUtils.toRel(getRelBuilder, input, catalogSink, sink, table)
} match {
case Some(sinkRel) => sinkRel
case None =>
throw new TableException(s"Sink ${catalogSink.getTableIdentifier} does not exists")
}
case outputConversion: OutputConversionModifyOperation =>
val input = getRelBuilder.queryOperation(outputConversion.getChild).build()
val (needUpdateBefore, withChangeFlag) = outputConversion.getUpdateMode match {
case UpdateMode.RETRACT => (true, true)
case UpdateMode.APPEND => (false, false)
case UpdateMode.UPSERT => (false, true)
}
val typeInfo = LegacyTypeInfoDataTypeConverter.toLegacyTypeInfo(outputConversion.getType)
val inputLogicalType = FlinkTypeFactory.toLogicalRowType(input.getRowType)
val sinkPhysicalSchema = inferSinkPhysicalSchema(
outputConversion.getType,
inputLogicalType,
withChangeFlag)
// validate query schema and sink schema, and apply cast if possible
val query = validateSchemaAndApplyImplicitCast(
input,
sinkPhysicalSchema,
null,
getTypeFactory)
val tableSink = new DataStreamTableSink(
FlinkTypeFactory.toTableSchema(query.getRowType),
typeInfo,
needUpdateBefore,
withChangeFlag)
LogicalLegacySink.create(
query,
tableSink,
"DataStreamTableSink",
ConnectorCatalogTable.sink(tableSink, !isStreamingMode))
case _ =>
throw new TableException(s"Unsupported ModifyOperation: $modifyOperation")
}
}
@VisibleForTesting
private[flink] def optimize(relNodes: Seq[RelNode]): Seq[RelNode] = {
val optimizedRelNodes = getOptimizer.optimize(relNodes)
require(optimizedRelNodes.size == relNodes.size)
optimizedRelNodes
}
@VisibleForTesting
private[flink] def optimize(relNode: RelNode): RelNode = {
val optimizedRelNodes = getOptimizer.optimize(Seq(relNode))
require(optimizedRelNodes.size == 1)
optimizedRelNodes.head
}
/**
* Converts [[FlinkPhysicalRel]] DAG to [[ExecNode]] DAG, and tries to reuse duplicate sub-plans.
*/
@VisibleForTesting
private[flink] def translateToExecNodePlan(
optimizedRelNodes: Seq[RelNode]): util.List[ExecNode[_, _]] = {
require(optimizedRelNodes.forall(_.isInstanceOf[FlinkPhysicalRel]))
// Rewrite same rel object to different rel objects
// in order to get the correct dag (dag reuse is based on object not digest)
val shuttle = new SameRelObjectShuttle()
val relsWithoutSameObj = optimizedRelNodes.map(_.accept(shuttle))
// reuse subplan
val reusedPlan = SubplanReuser.reuseDuplicatedSubplan(relsWithoutSameObj, config)
// convert FlinkPhysicalRel DAG to ExecNode DAG
reusedPlan.map(_.asInstanceOf[ExecNode[_, _]])
}
/**
* Translates a [[ExecNode]] DAG into a [[Transformation]] DAG.
*
* @param execNodes The node DAG to translate.
* @return The [[Transformation]] DAG that corresponds to the node DAG.
*/
protected def translateToPlan(execNodes: util.List[ExecNode[_, _]]): util.List[Transformation[_]]
/**
* Creates a [[SelectTableSinkBase]] for a select query.
*
* @param tableSchema the table schema of select result.
* @return The sink to fetch the select result.
*/
protected def createSelectTableSink(tableSchema: TableSchema): SelectTableSinkBase[_]
private def getTableSink(
objectIdentifier: ObjectIdentifier,
dynamicOptions: JMap[String, String])
: Option[(CatalogTable, Any)] = {
val lookupResult = JavaScalaConversionUtil.toScala(catalogManager.getTable(objectIdentifier))
lookupResult
.map(_.getTable) match {
case Some(table: ConnectorCatalogTable[_, _]) =>
JavaScalaConversionUtil.toScala(table.getTableSink) match {
case Some(sink) => Some(table, sink)
case None => None
}
case Some(table: CatalogTable) =>
val catalog = catalogManager.getCatalog(objectIdentifier.getCatalogName)
val tableToFind = if (dynamicOptions.nonEmpty) {
table.copy(FlinkHints.mergeTableOptions(dynamicOptions, table.getProperties))
} else {
table
}
val isTemporary = lookupResult.get.isTemporary
if (isLegacyConnectorOptions(objectIdentifier, table, isTemporary)) {
val tableSink = TableFactoryUtil.findAndCreateTableSink(
catalog.orElse(null),
objectIdentifier,
tableToFind,
getTableConfig.getConfiguration,
isStreamingMode,
isTemporary)
Option(table, tableSink)
} else {
val tableSink = FactoryUtil.createTableSink(
catalog.orElse(null),
objectIdentifier,
tableToFind,
getTableConfig.getConfiguration,
Thread.currentThread().getContextClassLoader,
isTemporary)
Option(table, tableSink)
}
case _ => None
}
}
/**
* Checks whether the [[CatalogTable]] uses legacy connector sink options.
*/
private def isLegacyConnectorOptions(
objectIdentifier: ObjectIdentifier,
catalogTable: CatalogTable,
isTemporary: Boolean) = {
// normalize option keys
val properties = new DescriptorProperties(true)
properties.putProperties(catalogTable.getOptions)
if (properties.containsKey(ConnectorDescriptorValidator.CONNECTOR_TYPE)) {
true
} else {
val catalog = catalogManager.getCatalog(objectIdentifier.getCatalogName)
try {
// try to create legacy table source using the options,
// some legacy factories uses the new 'connector' key
TableFactoryUtil.findAndCreateTableSink(
catalog.orElse(null),
objectIdentifier,
catalogTable,
getTableConfig.getConfiguration,
isStreamingMode,
isTemporary)
// success, then we will use the legacy factories
true
} catch {
// fail, then we will use new factories
case _: Throwable => false
}
}
}
}
示例：
select /*+ task(50) */
tumble_start(ts,interval '2' second) start_time,
tumble_end(ts,interval '2' second) end_time,
count(*) cnt
from
kafka_log
group by tumble(ts,interval '2' second)
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