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https://issues.apache.org/jira/browse/FLINK-5803?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15882982#comment-15882982
]
ASF GitHub Bot commented on FLINK-5803:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3397#discussion_r102968906
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/aggregate/UnboundedProcessingOverProcessFunction.scala
---
@@ -0,0 +1,105 @@
+/*
+ * 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.runtime.aggregate
+
+import org.apache.flink.api.common.typeinfo.TypeInformation
+import org.apache.flink.configuration.Configuration
+import org.apache.flink.streaming.api.functions.ProcessFunction.{Context,
OnTimerContext}
+import org.apache.flink.types.Row
+import org.apache.flink.streaming.api.functions.RichProcessFunction
+import org.apache.flink.util.{Collector, Preconditions}
+import org.apache.flink.api.common.typeutils.TypeSerializer
+import org.apache.flink.api.common.state.ValueStateDescriptor
+import org.apache.flink.api.java.typeutils.RowTypeInfo
+import org.apache.flink.api.common.state.ValueState
+import org.apache.flink.api.java.typeutils.runtime.RowSerializer
+
+class UnboundedProcessingOverProcessFunction(
+ private val aggregates: Array[Aggregate[_]],
+ private val projectionsMapping: Array[(Int, Int)],
+ private val aggregateMapping: Array[(Int, Int)],
+ private val intermediateRowType: RowTypeInfo,
+ @transient private val returnType: TypeInformation[Row])
+ extends RichProcessFunction[Row, Row]{
+
+ protected var stateSerializer: TypeSerializer[Row] = _
+ protected var stateDescriptor: ValueStateDescriptor[Row] = _
+
+ private var output: Row = _
+ private var state: ValueState[Row] = _
+
+ override def open(config: Configuration) {
+ Preconditions.checkNotNull(aggregates)
+ Preconditions.checkNotNull(projectionsMapping)
+ Preconditions.checkNotNull(aggregateMapping)
+ Preconditions.checkArgument(aggregates.length ==
aggregateMapping.length)
+
+ val finalRowLength: Int = projectionsMapping.length +
aggregateMapping.length
+ output = new Row(finalRowLength)
+ stateSerializer =
intermediateRowType.createSerializer(getRuntimeContext.getExecutionConfig)
+ stateDescriptor = new ValueStateDescriptor[Row]("overState",
stateSerializer)
+
+ }
+
+ override def processElement(
+ value2: Row,
+ ctx: Context,
+ out: Collector[Row]): Unit = {
+ state = getRuntimeContext.getState(stateDescriptor)
--- End diff --
We can do the `getState()` in the `open()` method and store the state in a
`transitive` member variable.
> Add [partitioned] processing time OVER RANGE BETWEEN UNBOUNDED PRECEDING
> aggregation to SQL
> -------------------------------------------------------------------------------------------
>
> Key: FLINK-5803
> URL: https://issues.apache.org/jira/browse/FLINK-5803
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: sunjincheng
> Assignee: sunjincheng
>
> The goal of this issue is to add support for OVER RANGE aggregations on
> processing time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT
> a,
> SUM(b) OVER (PARTITION BY c ORDER BY procTime() RANGE BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY procTime() RANGE BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The ORDER BY clause may only have procTime() as parameter. procTime() is a
> parameterless scalar function that just indicates processing time mode.
> - bounded PRECEDING is not supported (see FLINK-5654)
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some
> of the restrictions are trivial to address, we can add the functionality in
> this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with
> RexOver expression).
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