org.apache.flink.table.api.java.StreamTableEnvironment.scala Maven / Gradle / Ivy
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* distributed with this work for additional information
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* 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.api.java
import _root_.java.lang.{Boolean => JBool}
import org.apache.flink.api.common.typeinfo.TypeInformation
import org.apache.flink.api.java.tuple.{Tuple2 => JTuple2}
import org.apache.flink.streaming.api.datastream.DataStream
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment
import org.apache.flink.table.api._
import org.apache.flink.table.api.scala._
import org.apache.flink.table.api.types.DataTypes
import org.apache.flink.table.expressions.ExpressionParser
/**
* The [[TableEnvironment]] for a Java [[StreamExecutionEnvironment]].
*
* A TableEnvironment can be used to:
* - convert a [[DataStream]] to a [[Table]]
* - register a [[DataStream]] in the [[TableEnvironment]]'s catalog
* - register a [[Table]] in the [[TableEnvironment]]'s catalog
* - scan a registered table to obtain a [[Table]]
* - specify a SQL query on registered tables to obtain a [[Table]]
* - convert a [[Table]] into a [[DataStream]]
* - explain the AST and execution plan of a [[Table]]
*
* @param execEnv The Java [[StreamExecutionEnvironment]] of the TableEnvironment.
* @param config The configuration of the TableEnvironment.
*/
class StreamTableEnvironment(
execEnv: StreamExecutionEnvironment,
config: TableConfig)
extends org.apache.flink.table.api.StreamTableEnvironment(execEnv, config) {
/**
* Converts the given [[DataStream]] into a [[Table]].
*
* The field names of the [[Table]] are automatically derived from the type of the
* [[DataStream]].
*
* @param dataStream The [[DataStream]] to be converted.
* @tparam T The type of the [[DataStream]].
* @return The converted [[Table]].
*/
def fromDataStream[T](dataStream: DataStream[T]): Table = {
val name = createUniqueTableName()
registerDataStreamInternal(name, dataStream, false)
scan(name)
}
/**
* Converts the given [[DataStream]] into a [[Table]] with specified field names.
*
* Example:
*
* {{{
* DataStream> stream = ...
* Table tab = tableEnv.fromDataStream(stream, "a, b")
* }}}
*
* @param dataStream The [[DataStream]] to be converted.
* @param fields The field names of the resulting [[Table]].
* @tparam T The type of the [[DataStream]].
* @return The converted [[Table]].
*/
def fromDataStream[T](dataStream: DataStream[T], fields: String): Table = {
val exprs = ExpressionParser
.parseExpressionList(fields)
.toArray
val name = createUniqueTableName()
registerDataStreamInternal(name, dataStream, exprs, false)
scan(name)
}
/**
* Registers the given [[DataStream]] as table in the
* [[TableEnvironment]]'s catalog.
* Registered tables can be referenced in SQL queries.
*
* The field names of the [[Table]] are automatically derived
* from the type of the [[DataStream]].
*
* @param name The name under which the [[DataStream]] is registered in the catalog.
* @param dataStream The [[DataStream]] to register.
* @tparam T The type of the [[DataStream]] to register.
*/
def registerDataStream[T](name: String, dataStream: DataStream[T]): Unit = {
checkValidTableName(name)
registerDataStreamInternal(name, dataStream, false)
}
/**
* Registers or replace the given [[DataStream]] as table in the
* [[TableEnvironment]]'s catalog.
* Registered tables can be referenced in SQL queries.
*
* The field names of the [[Table]] are automatically derived
* from the type of the [[DataStream]].
*
* @param name The name under which the [[DataStream]] is registered in the catalog.
* @param dataStream The [[DataStream]] to register.
* @tparam T The type of the [[DataStream]] to register.
*/
def registerOrReplaceDataStream[T](name: String, dataStream: DataStream[T]): Unit = {
checkValidTableName(name)
registerDataStreamInternal(name, dataStream, true)
}
/**
* Registers the given [[DataStream]] as table with specified field names in the
* [[TableEnvironment]]'s catalog.
* Registered tables can be referenced in SQL queries.
*
* Example:
*
* {{{
* DataStream> set = ...
* tableEnv.registerDataStream("myTable", set, "a, b")
* }}}
*
* @param name The name under which the [[DataStream]] is registered in the catalog.
* @param dataStream The [[DataStream]] to register.
* @param fields The field names of the registered table.
* @tparam T The type of the [[DataStream]] to register.
*/
def registerDataStream[T](name: String, dataStream: DataStream[T], fields: String): Unit = {
val exprs = ExpressionParser
.parseExpressionList(fields)
.toArray
checkValidTableName(name)
registerDataStreamInternal(name, dataStream, exprs, false)
}
def registerOrReplaceDataStream[T](name: String,
dataStream: DataStream[T],
fields: String): Unit = {
val exprs = ExpressionParser
.parseExpressionList(fields)
.toArray
checkValidTableName(name)
registerDataStreamInternal(name, dataStream, exprs, true)
}
/**
* Converts the given [[Table]] into an append [[DataStream]] of a specified type.
*
* The [[Table]] must only have insert (append) changes. If the [[Table]] is also modified
* by update or delete changes, the conversion will fail.
*
* The fields of the [[Table]] are mapped to [[DataStream]] fields as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param clazz The class of the type of the resulting [[DataStream]].
* @tparam T The type of the resulting [[DataStream]].
* @return The converted [[DataStream]].
*/
def toAppendStream[T](table: Table, clazz: Class[T]): DataStream[T] = {
val t = DataTypes.extractDataType(clazz)
TableEnvironment.validateType(t)
translateToDataStream[T](table, updatesAsRetraction = false, withChangeFlag = false, t)
}
/**
* Converts the given [[Table]] into an append [[DataStream]] of a specified type.
*
* The [[Table]] must only have insert (append) changes. If the [[Table]] is also modified
* by update or delete changes, the conversion will fail.
*
* The fields of the [[Table]] are mapped to [[DataStream]] fields as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param typeInfo The [[TypeInformation]] that specifies the type of the [[DataStream]].
* @tparam T The type of the resulting [[DataStream]].
* @return The converted [[DataStream]].
*/
def toAppendStream[T](table: Table, typeInfo: TypeInformation[T]): DataStream[T] = {
TableEnvironment.validateType(typeInfo)
translateToDataStream[T](table, updatesAsRetraction = false, withChangeFlag = false, typeInfo)
}
/**
* Converts the given [[Table]] into an append [[DataStream]] of a specified type.
*
* The [[Table]] must only have insert (append) changes. If the [[Table]] is also modified
* by update or delete changes, the conversion will fail.
*
* The fields of the [[Table]] are mapped to [[DataStream]] fields as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param clazz The class of the type of the resulting [[DataStream]].
* @param queryConfig The configuration of the query to generate.
* @tparam T The type of the resulting [[DataStream]].
* @return The converted [[DataStream]].
*/
def toAppendStream[T](
table: Table,
clazz: Class[T],
queryConfig: StreamQueryConfig): DataStream[T] = {
queryConfig.overrideTableConfig(getConfig)
toAppendStream(table, clazz)
}
/**
* Converts the given [[Table]] into an append [[DataStream]] of a specified type.
*
* The [[Table]] must only have insert (append) changes. If the [[Table]] is also modified
* by update or delete changes, the conversion will fail.
*
* The fields of the [[Table]] are mapped to [[DataStream]] fields as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param typeInfo The [[TypeInformation]] that specifies the type of the [[DataStream]].
* @param queryConfig The configuration of the query to generate.
* @tparam T The type of the resulting [[DataStream]].
* @return The converted [[DataStream]].
*/
def toAppendStream[T](
table: Table,
typeInfo: TypeInformation[T],
queryConfig: StreamQueryConfig): DataStream[T] = {
toAppendStream(table, typeInfo)
}
/**
* Converts the given [[Table]] into a [[DataStream]] of add and retract messages.
* The message will be encoded as [[JTuple2]]. The first field is a [[JBool]] flag,
* the second field holds the record of the specified type [[T]].
*
* A true [[JBool]] flag indicates an add message, a false flag indicates a retract message.
*
* The fields of the [[Table]] are mapped to the requested type as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param clazz The class of the requested record type.
* @tparam T The type of the requested record type.
* @return The converted [[DataStream]].
*/
def toRetractStream[T](
table: Table,
clazz: Class[T]): DataStream[JTuple2[JBool, T]] = {
val tp = DataTypes.extractDataType(clazz)
TableEnvironment.validateType(tp)
translateToDataStream[JTuple2[JBool, T]](
table,
updatesAsRetraction = true,
withChangeFlag = true,
DataTypes.createTupleType(DataTypes.BOOLEAN, tp))
}
/**
* Converts the given [[Table]] into a [[DataStream]] of add and retract messages.
* The message will be encoded as [[JTuple2]]. The first field is a [[JBool]] flag,
* the second field holds the record of the specified type [[T]].
*
* A true [[JBool]] flag indicates an add message, a false flag indicates a retract message.
*
* The fields of the [[Table]] are mapped to the requested type as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param typeInfo The [[TypeInformation]] of the requested record type.
* @tparam T The type of the requested record type.
* @return The converted [[DataStream]].
*/
def toRetractStream[T](
table: Table,
typeInfo: TypeInformation[T]): DataStream[JTuple2[JBool, T]] = {
TableEnvironment.validateType(typeInfo)
translateToDataStream[JTuple2[JBool, T]](
table,
updatesAsRetraction = true,
withChangeFlag = true,
DataTypes.createTupleType(DataTypes.BOOLEAN, typeInfo))
}
/**
* Converts the given [[Table]] into a [[DataStream]] of add and retract messages.
* The message will be encoded as [[JTuple2]]. The first field is a [[JBool]] flag,
* the second field holds the record of the specified type [[T]].
*
* A true [[JBool]] flag indicates an add message, a false flag indicates a retract message.
*
* The fields of the [[Table]] are mapped to the requested type as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param clazz The class of the requested record type.
* @param queryConfig The configuration of the query to generate.
* @tparam T The type of the requested record type.
* @return The converted [[DataStream]].
*/
def toRetractStream[T](
table: Table,
clazz: Class[T],
queryConfig: StreamQueryConfig): DataStream[JTuple2[JBool, T]] = {
queryConfig.overrideTableConfig(getConfig)
toRetractStream(table, clazz)
}
/**
* Converts the given [[Table]] into a [[DataStream]] of add and retract messages.
* The message will be encoded as [[JTuple2]]. The first field is a [[JBool]] flag,
* the second field holds the record of the specified type [[T]].
*
* A true [[JBool]] flag indicates an add message, a false flag indicates a retract message.
*
* The fields of the [[Table]] are mapped to the requested type as follows:
* - [[org.apache.flink.types.Row]] and [[org.apache.flink.api.java.tuple.Tuple]]
* types: Fields are mapped by position, field types must match.
* - POJO [[DataStream]] types: Fields are mapped by field name, field types must match.
*
* @param table The [[Table]] to convert.
* @param typeInfo The [[TypeInformation]] of the requested record type.
* @param queryConfig The configuration of the query to generate.
* @tparam T The type of the requested record type.
* @return The converted [[DataStream]].
*/
def toRetractStream[T](
table: Table,
typeInfo: TypeInformation[T],
queryConfig: StreamQueryConfig): DataStream[JTuple2[JBool, T]] = {
queryConfig.overrideTableConfig(getConfig)
toRetractStream(table, typeInfo)
}
}
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