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https://issues.apache.org/jira/browse/BEAM-9822?focusedWorklogId=435627&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-435627
]
ASF GitHub Bot logged work on BEAM-9822:
----------------------------------------
Author: ASF GitHub Bot
Created on: 20/May/20 19:09
Start Date: 20/May/20 19:09
Worklog Time Spent: 10m
Work Description: nielm commented on a change in pull request #11529:
URL: https://github.com/apache/beam/pull/11529#discussion_r428246820
##########
File path:
sdks/java/io/google-cloud-platform/src/test/java/org/apache/beam/sdk/io/gcp/spanner/SpannerIOWriteTest.java
##########
@@ -263,6 +263,17 @@ private void verifyBatches(Iterable<Mutation>... batches) {
@Test
public void noBatching() throws Exception {
+
+ // This test uses a different mock/fake because it explicitly does not
want to populate the
+ // Spanner schema.
+ FakeServiceFactory fakeServiceFactory = new FakeServiceFactory();
+ ReadOnlyTransaction tx = mock(ReadOnlyTransaction.class);
+
when(fakeServiceFactory.mockDatabaseClient().readOnlyTransaction()).thenReturn(tx);
+
+ // Capture batches sent to writeAtLeastOnce.
+
when(fakeServiceFactory.mockDatabaseClient().writeAtLeastOnce(mutationBatchesCaptor.capture()))
+ .thenReturn(null);
+
Review comment:
Oops, yes, correct. Fixed now.
> Ah I see. But should you be using `fakeServiceFactory` throughout this
test then? There are still references to `serviceFactory`
Oops, yes, correct! Fixed now.
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Issue Time Tracking
-------------------
Worklog Id: (was: 435627)
Time Spent: 7.5h (was: 7h 20m)
> SpannerIO: Reduce memory usage - especially when streaming
> ----------------------------------------------------------
>
> Key: BEAM-9822
> URL: https://issues.apache.org/jira/browse/BEAM-9822
> Project: Beam
> Issue Type: Bug
> Components: io-java-gcp
> Affects Versions: 2.20.0, 2.21.0
> Reporter: Niel Markwick
> Assignee: Niel Markwick
> Priority: P2
> Labels: google-cloud-spanner
> Fix For: 2.22.0
>
> Time Spent: 7.5h
> Remaining Estimate: 0h
>
> SpannerIO uses a lot of memory.
> In Streaming Dataflow, it uses many times as much (because dataflow creates
> many worker threads)
> Lower the memory use, and change default parameters during streaming to use
> smaller batches and disable grouping.
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