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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Work logged] (BEAM-3193) CoGroupByKey doesn't work in streaming mode
Date Tue, 04 Sep 2018 12:47:00 GMT

     [ https://issues.apache.org/jira/browse/BEAM-3193?focusedWorklogId=140891&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-140891
]

ASF GitHub Bot logged work on BEAM-3193:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 04/Sep/18 12:46
            Start Date: 04/Sep/18 12:46
    Worklog Time Spent: 10m 
      Work Description: echauchot closed pull request #5945: [BEAM-3193] Add SparkCoGroupByKeyStreaming
validates runner to test CoGroupByKay bahavior in streaming mode on spark runner
URL: https://github.com/apache/beam/pull/5945
 
 
   

This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:

As this is a foreign pull request (from a fork), the diff is supplied
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diff --git a/runners/spark/src/test/java/org/apache/beam/runners/spark/translation/streaming/SparkCoGroupByKeyStreamingTest.java
b/runners/spark/src/test/java/org/apache/beam/runners/spark/translation/streaming/SparkCoGroupByKeyStreamingTest.java
new file mode 100644
index 00000000000..b89519fe0ff
--- /dev/null
+++ b/runners/spark/src/test/java/org/apache/beam/runners/spark/translation/streaming/SparkCoGroupByKeyStreamingTest.java
@@ -0,0 +1,172 @@
+/*
+ * 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.beam.runners.spark.translation.streaming;
+
+import static org.hamcrest.Matchers.containsInAnyOrder;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertThat;
+import static org.junit.Assert.fail;
+
+import com.google.common.collect.Iterables;
+import org.apache.beam.runners.spark.ReuseSparkContextRule;
+import org.apache.beam.runners.spark.SparkPipelineOptions;
+import org.apache.beam.runners.spark.StreamingTest;
+import org.apache.beam.runners.spark.io.CreateStream;
+import org.apache.beam.sdk.coders.KvCoder;
+import org.apache.beam.sdk.coders.VarIntCoder;
+import org.apache.beam.sdk.testing.PAssert;
+import org.apache.beam.sdk.testing.TestPipeline;
+import org.apache.beam.sdk.transforms.SerializableFunction;
+import org.apache.beam.sdk.transforms.join.CoGbkResult;
+import org.apache.beam.sdk.transforms.join.CoGroupByKey;
+import org.apache.beam.sdk.transforms.join.KeyedPCollectionTuple;
+import org.apache.beam.sdk.transforms.windowing.FixedWindows;
+import org.apache.beam.sdk.transforms.windowing.Window;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.TimestampedValue;
+import org.apache.beam.sdk.values.TupleTag;
+import org.joda.time.Duration;
+import org.joda.time.Instant;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.experimental.categories.Category;
+
+/** A test that verifies that CoGroupByKey works in streaming mode in spark runner. */
+public class SparkCoGroupByKeyStreamingTest {
+
+  private static final TupleTag<Integer> INPUT1_TAG = new TupleTag<>("input1");
+  private static final TupleTag<Integer> INPUT2_TAG = new TupleTag<>("input2");
+
+  @Rule public final transient ReuseSparkContextRule noContextResue = ReuseSparkContextRule.no();
+
+  @Rule public final TestPipeline pipeline = TestPipeline.create();
+
+  private Duration batchDuration() {
+    return Duration.millis(
+        (pipeline.getOptions().as(SparkPipelineOptions.class)).getBatchIntervalMillis());
+  }
+
+  @Category(StreamingTest.class)
+  @Test
+  public void testInStreamingMode() throws Exception {
+    Instant instant = new Instant(0);
+    CreateStream<KV<Integer, Integer>> source1 =
+        CreateStream.of(KvCoder.of(VarIntCoder.of(), VarIntCoder.of()), batchDuration())
+            .emptyBatch()
+            .advanceWatermarkForNextBatch(instant)
+            .nextBatch(
+                TimestampedValue.of(KV.of(1, 1), instant),
+                TimestampedValue.of(KV.of(1, 2), instant),
+                TimestampedValue.of(KV.of(1, 3), instant))
+            .advanceWatermarkForNextBatch(instant.plus(Duration.standardSeconds(1L)))
+            .nextBatch(
+                TimestampedValue.of(KV.of(2, 4), instant.plus(Duration.standardSeconds(1L))),
+                TimestampedValue.of(KV.of(2, 5), instant.plus(Duration.standardSeconds(1L))),
+                TimestampedValue.of(KV.of(2, 6), instant.plus(Duration.standardSeconds(1L))))
+            .advanceNextBatchWatermarkToInfinity();
+
+    CreateStream<KV<Integer, Integer>> source2 =
+        CreateStream.of(KvCoder.of(VarIntCoder.of(), VarIntCoder.of()), batchDuration())
+            .emptyBatch()
+            .advanceWatermarkForNextBatch(instant)
+            .nextBatch(
+                TimestampedValue.of(KV.of(1, 11), instant),
+                TimestampedValue.of(KV.of(1, 12), instant),
+                TimestampedValue.of(KV.of(1, 13), instant))
+            .advanceWatermarkForNextBatch(instant.plus(Duration.standardSeconds(1L)))
+            .nextBatch(
+                TimestampedValue.of(KV.of(2, 14), instant.plus(Duration.standardSeconds(1L))),
+                TimestampedValue.of(KV.of(2, 15), instant.plus(Duration.standardSeconds(1L))),
+                TimestampedValue.of(KV.of(2, 16), instant.plus(Duration.standardSeconds(1L))))
+            .advanceNextBatchWatermarkToInfinity();
+
+    PCollection<KV<Integer, Integer>> input1 =
+        pipeline
+            .apply("create source1", source1)
+            .apply(
+                "window input1",
+                Window.<KV<Integer, Integer>>into(FixedWindows.of(Duration.standardSeconds(3L)))
+                    .withAllowedLateness(Duration.ZERO));
+
+    PCollection<KV<Integer, Integer>> input2 =
+        pipeline
+            .apply("create source2", source2)
+            .apply(
+                "window input2",
+                Window.<KV<Integer, Integer>>into(FixedWindows.of(Duration.standardSeconds(3L)))
+                    .withAllowedLateness(Duration.ZERO));
+
+    PCollection<KV<Integer, CoGbkResult>> output =
+        KeyedPCollectionTuple.of(INPUT1_TAG, input1)
+            .and(INPUT2_TAG, input2)
+            .apply(CoGroupByKey.create());
+    PAssert.that("Wrong output of the join using CoGroupByKey in streaming mode", output)
+        .satisfies(
+            (SerializableFunction<Iterable<KV<Integer, CoGbkResult>>, Void>)
+                input -> {
+                  assertEquals("Wrong size of the output PCollection", 2, Iterables.size(input));
+                  for (KV<Integer, CoGbkResult> element : input) {
+                    if (element.getKey() == 1) {
+                      Iterable<Integer> input1Elements = element.getValue().getAll(INPUT1_TAG);
+                      assertEquals(
+                          "Wrong number of values for output elements for tag input1 and
key 1",
+                          3,
+                          Iterables.size(input1Elements));
+                      assertThat(
+                          "Elements of PCollection input1 for key \"1\" are not present in
the output PCollection",
+                          input1Elements,
+                          containsInAnyOrder(1, 2, 3));
+                      Iterable<Integer> input2Elements = element.getValue().getAll(INPUT2_TAG);
+                      assertEquals(
+                          "Wrong number of values for output elements for tag input2 and
key 1",
+                          3,
+                          Iterables.size(input2Elements));
+                      assertThat(
+                          "Elements of PCollection input2 for key \"1\" are not present in
the output PCollection",
+                          input2Elements,
+                          containsInAnyOrder(11, 12, 13));
+                    } else if (element.getKey() == 2) {
+                      Iterable<Integer> input1Elements = element.getValue().getAll(INPUT1_TAG);
+                      assertEquals(
+                          "Wrong number of values for output elements for tag input1 and
key 2",
+                          3,
+                          Iterables.size(input1Elements));
+                      assertThat(
+                          "Elements of PCollection input1 for key \"2\" are not present in
the output PCollection",
+                          input1Elements,
+                          containsInAnyOrder(4, 5, 6));
+                      Iterable<Integer> input2Elements = element.getValue().getAll(INPUT2_TAG);
+                      assertEquals(
+                          "Wrong number of values for output elements for tag input2 and
key 2",
+                          3,
+                          Iterables.size(input2Elements));
+                      assertThat(
+                          "Elements of PCollection input2 for key \"2\" are not present in
the output PCollection",
+                          input2Elements,
+                          containsInAnyOrder(14, 15, 16));
+                    } else {
+                      fail("Unknown key in the output PCollection");
+                    }
+                  }
+                  return null;
+                });
+    pipeline.run();
+  }
+}


 

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Issue Time Tracking
-------------------

    Worklog Id:     (was: 140891)
    Time Spent: 3h 50m  (was: 3h 40m)

> CoGroupByKey doesn't work in streaming mode
> -------------------------------------------
>
>                 Key: BEAM-3193
>                 URL: https://issues.apache.org/jira/browse/BEAM-3193
>             Project: Beam
>          Issue Type: Bug
>          Components: runner-spark
>            Reporter: Jean-Baptiste Onofré
>            Assignee: Etienne Chauchot
>            Priority: Major
>          Time Spent: 3h 50m
>  Remaining Estimate: 0h
>
> The CoGroupByKey PTransform doesn't throw an exception but doesn't actually perform the
grouping when used in streaming mode. I will attach a test pipeline.



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