[
https://issues.apache.org/jira/browse/BEAM-7131?focusedWorklogId=247116&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-247116
]
ASF GitHub Bot logged work on BEAM-7131:
----------------------------------------
Author: ASF GitHub Bot
Created on: 22/May/19 22:48
Start Date: 22/May/19 22:48
Worklog Time Spent: 10m
Work Description: ibzib commented on pull request #8558: [BEAM-7131]
Spark: cache executable stage output to prevent re-computation
URL: https://github.com/apache/beam/pull/8558#discussion_r286666450
##########
File path:
runners/spark/src/test/java/org/apache/beam/runners/spark/SparkPortableExecutionTest.java
##########
@@ -159,8 +162,166 @@ public void process(ProcessContext context) {
pipelineProto,
options.as(SparkPipelineOptions.class));
jobInvocation.start();
- while (jobInvocation.getState() != Enum.DONE) {
- Thread.sleep(1000);
- }
+ Assert.assertEquals(Enum.DONE, jobInvocation.getState());
+ }
+
+ /**
+ * Verifies that each executable stage runs exactly once, even if that
executable stage has
+ * multiple immediate outputs. While re-computation may be necessary in the
event of failure,
+ * re-computation of a whole executable stage is expensive and can cause
unexpected behavior when
+ * the executable stage has side effects (BEAM-7131).
+ *
+ * <pre>
+ * |-> B -> GBK
+ * A -|
+ * |-> C -> GBK
+ * </pre>
+ */
+ @Test(timeout = 120_000)
+ public void testExecStageWithMultipleOutputs() throws Exception {
+ PipelineOptions options = PipelineOptionsFactory.create();
+ options.setRunner(CrashingRunner.class);
+ options
+ .as(PortablePipelineOptions.class)
+ .setDefaultEnvironmentType(Environments.ENVIRONMENT_EMBEDDED);
+ Pipeline pipeline = Pipeline.create(options);
+ String path =
+ FileSystems.getDefault()
+ .getPath(temporaryFolder.getRoot().getAbsolutePath(),
UUID.randomUUID().toString())
+ .toString();
+ File file = new File(path);
+ PCollection<String> a =
+ pipeline
+ .apply("impulse", Impulse.create())
+ .apply(
+ "A",
+ ParDo.of(
+ new DoFn<byte[], String>() {
+ @ProcessElement
+ public void process(ProcessContext context) throws
Exception {
+ context.output("A");
+ // ParDos A, B, and C will all be fused together into
the same executable
+ // stage. This check verifies that stage is not run
more than once by
+ // enacting a side effect via the local file system.
+ Assert.assertTrue(
+ String.format(
+ "Create file %s failed (ParDo A should only
have been run once).",
+ path),
+ file.createNewFile());
+ }
+ }));
+ PCollection<KV<String, String>> b =
+ a.apply(
+ "B",
+ ParDo.of(
+ new DoFn<String, KV<String, String>>() {
+ @ProcessElement
+ public void process(ProcessContext context) {
+ context.output(KV.of(context.element(), "B"));
+ }
+ }));
+ PCollection<KV<String, String>> c =
+ a.apply(
+ "C",
+ ParDo.of(
+ new DoFn<String, KV<String, String>>() {
+ @ProcessElement
+ public void process(ProcessContext context) {
+ context.output(KV.of(context.element(), "C"));
+ }
+ }));
+ // Use GBKs to force re-computation of executable stage unless cached.
+ b.apply(GroupByKey.create());
+ c.apply(GroupByKey.create());
+ RunnerApi.Pipeline pipelineProto = PipelineTranslation.toProto(pipeline);
+ JobInvocation jobInvocation =
+ SparkJobInvoker.createJobInvocation(
+ "testExecStageWithMultipleOutputs",
+ "testExecStageWithMultipleOutputsRetrievalToken",
+ sparkJobExecutor,
+ pipelineProto,
+ options.as(SparkPipelineOptions.class));
+ jobInvocation.start();
+ Assert.assertEquals(Enum.DONE, jobInvocation.getState());
+ Assert.assertTrue(file.exists());
+ }
+
+ /**
+ * Verifies that each executable stage runs exactly once, even if that
executable stage has
+ * multiple downstream consumers. While re-computation may be necessary in
the event of failure,
+ * re-computation of a whole executable stage is expensive and can cause
unexpected behavior when
+ * the executable stage has side effects (BEAM-7131).
+ *
+ * <pre>
+ * |-> B
+ * A -> GBK -|
+ * |-> C
+ * </pre>
+ */
+ @Test(timeout = 120_000)
+ public void testExecStageWithMultipleConsumers() throws Exception {
+ PipelineOptions options = PipelineOptionsFactory.create();
+ options.setRunner(CrashingRunner.class);
+ options
+ .as(PortablePipelineOptions.class)
+ .setDefaultEnvironmentType(Environments.ENVIRONMENT_EMBEDDED);
+ Pipeline pipeline = Pipeline.create(options);
+ String path =
+ FileSystems.getDefault()
+ .getPath(temporaryFolder.getRoot().getAbsolutePath(),
UUID.randomUUID().toString())
+ .toString();
+ File file = new File(path);
+ PCollection<KV<String, Integer>> a =
+ pipeline
+ .apply("impulse", Impulse.create())
+ .apply(
+ "A",
+ ParDo.of(
+ new DoFn<byte[], KV<String, Integer>>() {
Review comment:
Done
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Issue Time Tracking
-------------------
Worklog Id: (was: 247116)
Time Spent: 4h 10m (was: 4h)
> Spark portable runner appears to be repeating work (in TFX example)
> -------------------------------------------------------------------
>
> Key: BEAM-7131
> URL: https://issues.apache.org/jira/browse/BEAM-7131
> Project: Beam
> Issue Type: Bug
> Components: runner-spark
> Reporter: Kyle Weaver
> Assignee: Kyle Weaver
> Priority: Major
> Time Spent: 4h 10m
> Remaining Estimate: 0h
>
> I've been trying to run the TFX Chicago taxi example [1] on the Spark
> portable runner. TFDV works fine, but the preprocess step
> (preprocess_flink.sh [2]) fails with the following error:
> RuntimeError: AlreadyExistsError: file already exists [while running
> 'WriteTransformFn/WriteTransformFn']
> Assets are being written multiple times to different temp directories, which
> is okay, but the error occurs when they are copied to the same permanent
> output directory. Specifically, the copy tree operation in transform_fn_io.py
> [3] is run twice with the same output directory. The error doesn't occur when
> that code is modified to allow overwriting existing files, but that's only a
> shallow fix. While the TF transform should probably be made idempotent, this
> is also an issue with the Spark runner, which shouldn't be repeating work
> like this regularly (in the absence of a failure condition).
> [1] [https://github.com/tensorflow/tfx/tree/master/tfx/examples/chicago_taxi]
> [2]
> [https://github.com/tensorflow/tfx/blob/master/tfx/examples/chicago_taxi/preprocess_flink.sh]
> [3]
> [https://github.com/tensorflow/transform/blob/master/tensorflow_transform/beam/tft_beam_io/transform_fn_io.py#L33-L45]
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