This is an automated email from the ASF dual-hosted git repository.
aromanenko pushed a commit to branch spark-runner_structured-streaming
in repository https://gitbox.apache.org/repos/asf/beam.git
The following commit(s) were added to
refs/heads/spark-runner_structured-streaming by this push:
new 3533779 Fix spotlessJava issues
3533779 is described below
commit 353377986e9b0f006772de7639616fa58cca995c
Author: Alexey Romanenko <aromanenko....@gmail.com>
AuthorDate: Fri Dec 28 15:59:34 2018 +0100
Fix spotlessJava issues
---
.../translation/TranslationContext.java | 10 ++---
.../translation/batch/DatasetSourceBatch.java | 9 +++--
.../translation/batch/DatasetSourceMockBatch.java | 44 ++++++++++++----------
.../translation/batch/FlattenTranslatorBatch.java | 2 +-
.../batch/ReadSourceTranslatorBatch.java | 18 +++++----
.../batch/ReadSourceTranslatorMockBatch.java | 18 +++++----
.../streaming/DatasetSourceStreaming.java | 16 +-------
.../streaming/ReadSourceTranslatorStreaming.java | 22 +++++------
.../spark/structuredstreaming/SourceTest.java | 19 +++++++++-
9 files changed, 88 insertions(+), 70 deletions(-)
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/TranslationContext.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/TranslationContext.java
index acc49f4..5606886 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/TranslationContext.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/TranslationContext.java
@@ -115,12 +115,12 @@ public class TranslationContext {
}
}
- public void putDatasetRaw(PValue value, Dataset<WindowedValue> dataset) {
- if (!datasets.containsKey(value)) {
- datasets.put(value, dataset);
- leaves.add(dataset);
- }
+ public void putDatasetRaw(PValue value, Dataset<WindowedValue> dataset) {
+ if (!datasets.containsKey(value)) {
+ datasets.put(value, dataset);
+ leaves.add(dataset);
}
+ }
//
--------------------------------------------------------------------------------------------
// PCollections methods
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceBatch.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceBatch.java
index f4cd885..7726ad7 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceBatch.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceBatch.java
@@ -50,12 +50,13 @@ public class DatasetSourceBatch<T> implements DataSourceV2,
ReadSupport {
private TranslationContext context;
private BoundedSource<T> source;
-
- @Override public DataSourceReader createReader(DataSourceOptions options) {
+ @Override
+ public DataSourceReader createReader(DataSourceOptions options) {
this.numPartitions =
context.getSparkSession().sparkContext().defaultParallelism();
checkArgument(this.numPartitions > 0, "Number of partitions must be
greater than zero.");
this.bundleSize = context.getOptions().getBundleSize();
- return new DatasetReader(); }
+ return new DatasetReader();
+ }
/** This class can be mapped to Beam {@link BoundedSource}. */
private class DatasetReader implements DataSourceReader {
@@ -106,7 +107,7 @@ public class DatasetSourceBatch<T> implements DataSourceV2,
ReadSupport {
}
}
- /** This class can be mapped to Beam {@link BoundedReader} */
+ /** This class can be mapped to Beam {@link BoundedReader}. */
private class DatasetPartitionReader implements
InputPartitionReader<InternalRow> {
BoundedReader<T> reader;
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceMockBatch.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceMockBatch.java
index b616a6f..5485257 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceMockBatch.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/DatasetSourceMockBatch.java
@@ -34,58 +34,64 @@ import
org.apache.spark.sql.sources.v2.reader.InputPartitionReader;
import org.apache.spark.sql.types.StructType;
import org.joda.time.Instant;
-/**
- * This is a mock source that gives values between 0 and 999.
- */
+/** This is a mock source that gives values between 0 and 999. */
public class DatasetSourceMockBatch implements DataSourceV2, ReadSupport {
- @Override public DataSourceReader createReader(DataSourceOptions options) {
+ @Override
+ public DataSourceReader createReader(DataSourceOptions options) {
return new DatasetReader();
}
/** This class can be mapped to Beam {@link BoundedSource}. */
private static class DatasetReader implements DataSourceReader {
- @Override public StructType readSchema() {
+ @Override
+ public StructType readSchema() {
return new StructType();
}
- @Override public List<InputPartition<InternalRow>> planInputPartitions() {
+ @Override
+ public List<InputPartition<InternalRow>> planInputPartitions() {
List<InputPartition<InternalRow>> result = new ArrayList<>();
- result.add(new InputPartition<InternalRow>() {
+ result.add(
+ new InputPartition<InternalRow>() {
- @Override public InputPartitionReader<InternalRow>
createPartitionReader() {
- return new DatasetPartitionReaderMock();
- }
- });
+ @Override
+ public InputPartitionReader<InternalRow> createPartitionReader() {
+ return new DatasetPartitionReaderMock();
+ }
+ });
return result;
}
}
- /** This class is a mocked reader*/
+ /** This class is a mocked reader. */
private static class DatasetPartitionReaderMock implements
InputPartitionReader<InternalRow> {
private ArrayList<Integer> values;
private int currentIndex = 0;
private DatasetPartitionReaderMock() {
- for (int i = 0; i < 1000; i++){
+ for (int i = 0; i < 1000; i++) {
values.add(i);
}
}
- @Override public boolean next() throws IOException {
+ @Override
+ public boolean next() throws IOException {
currentIndex++;
return (currentIndex <= values.size());
}
- @Override public void close() throws IOException {
- }
+ @Override
+ public void close() throws IOException {}
- @Override public InternalRow get() {
+ @Override
+ public InternalRow get() {
List<Object> list = new ArrayList<>();
-
list.add(WindowedValue.timestampedValueInGlobalWindow(values.get(currentIndex),
new Instant()));
+ list.add(
+
WindowedValue.timestampedValueInGlobalWindow(values.get(currentIndex), new
Instant()));
return InternalRow.apply(asScalaBuffer(list).toList());
}
}
-}
\ No newline at end of file
+}
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/FlattenTranslatorBatch.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/FlattenTranslatorBatch.java
index 2739e83..b7b3541 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/FlattenTranslatorBatch.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/FlattenTranslatorBatch.java
@@ -45,7 +45,7 @@ class FlattenTranslatorBatch<T>
for (PValue pValue : inputs.values()) {
checkArgument(
pValue instanceof PCollection,
- "Got non-PCollection input to flatten: %s of type %s",
+ "Got non-PCollection input to flatten: %s of type %s",
pValue,
pValue.getClass().getSimpleName());
@SuppressWarnings("unchecked")
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorBatch.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorBatch.java
index d980a52..1aa5a2e 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorBatch.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorBatch.java
@@ -36,7 +36,7 @@ import org.apache.spark.sql.SparkSession;
class ReadSourceTranslatorBatch<T>
implements TransformTranslator<PTransform<PBegin, PCollection<T>>> {
- private String SOURCE_PROVIDER_CLASS =
DatasetSourceBatch.class.getCanonicalName();
+ private static final String SOURCE_PROVIDER_CLASS =
DatasetSourceBatch.class.getCanonicalName();
@SuppressWarnings("unchecked")
@Override
@@ -46,7 +46,7 @@ class ReadSourceTranslatorBatch<T>
(AppliedPTransform<PBegin, PCollection<T>, PTransform<PBegin,
PCollection<T>>>)
context.getCurrentTransform();
- BoundedSource<T> source;
+ BoundedSource<T> source;
try {
source = ReadTranslation.boundedSourceFromTransform(rootTransform);
} catch (IOException e) {
@@ -57,12 +57,14 @@ class ReadSourceTranslatorBatch<T>
Dataset<Row> rowDataset =
sparkSession.read().format(SOURCE_PROVIDER_CLASS).load();
//TODO pass the source and the translation context serialized as string to
the DatasetSource
- MapFunction<Row, WindowedValue> func = new MapFunction<Row,
WindowedValue>() {
- @Override public WindowedValue call(Row value) throws Exception {
- //there is only one value put in each Row by the InputPartitionReader
- return value.<WindowedValue>getAs(0);
- }
- };
+ MapFunction<Row, WindowedValue> func =
+ new MapFunction<Row, WindowedValue>() {
+ @Override
+ public WindowedValue call(Row value) throws Exception {
+ //there is only one value put in each Row by the
InputPartitionReader
+ return value.<WindowedValue>getAs(0);
+ }
+ };
//TODO: is there a better way than using the raw WindowedValue? Can an
Encoder<WindowedVAlue<T>>
// be created ?
Dataset<WindowedValue> dataset = rowDataset.map(func,
Encoders.kryo(WindowedValue.class));
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorMockBatch.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorMockBatch.java
index d7b9175..ca3356c 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorMockBatch.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/batch/ReadSourceTranslatorMockBatch.java
@@ -31,12 +31,14 @@ import org.apache.spark.sql.SparkSession;
/**
* Mock translator that generates a source of 0 to 999 and prints it.
+ *
* @param <T>
*/
class ReadSourceTranslatorMockBatch<T>
implements TransformTranslator<PTransform<PBegin, PCollection<T>>> {
- private String SOURCE_PROVIDER_CLASS =
DatasetSourceMockBatch.class.getCanonicalName();
+ private static final String SOURCE_PROVIDER_CLASS =
+ DatasetSourceMockBatch.class.getCanonicalName();
@SuppressWarnings("unchecked")
@Override
@@ -46,12 +48,14 @@ class ReadSourceTranslatorMockBatch<T>
Dataset<Row> rowDataset =
sparkSession.read().format(SOURCE_PROVIDER_CLASS).load();
- MapFunction<Row, WindowedValue> func = new MapFunction<Row,
WindowedValue>() {
- @Override public WindowedValue call(Row value) throws Exception {
- //there is only one value put in each Row by the InputPartitionReader
- return value.<WindowedValue>getAs(0);
- }
- };
+ MapFunction<Row, WindowedValue> func =
+ new MapFunction<Row, WindowedValue>() {
+ @Override
+ public WindowedValue call(Row value) throws Exception {
+ //there is only one value put in each Row by the
InputPartitionReader
+ return value.<WindowedValue>getAs(0);
+ }
+ };
//TODO: is there a better way than using the raw WindowedValue? Can an
Encoder<WindowedVAlue<T>>
// be created ?
Dataset<WindowedValue> dataset = rowDataset.map(func,
Encoders.kryo(WindowedValue.class));
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/DatasetSourceStreaming.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/DatasetSourceStreaming.java
index fad68d3..b43f53c 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/DatasetSourceStreaming.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/DatasetSourceStreaming.java
@@ -28,16 +28,7 @@ import
org.apache.beam.runners.spark.structuredstreaming.SparkPipelineOptions;
import
org.apache.beam.runners.spark.structuredstreaming.translation.TranslationContext;
import org.apache.beam.sdk.io.BoundedSource;
import org.apache.beam.sdk.io.BoundedSource.BoundedReader;
-import org.apache.beam.sdk.io.Source;
import org.apache.beam.sdk.util.WindowedValue;
-import org.apache.spark.sql.AnalysisException;
-import org.apache.spark.sql.Dataset;
-import org.apache.spark.sql.Row;
-import org.apache.spark.sql.catalog.Catalog;
-import org.apache.spark.sql.catalog.Column;
-import org.apache.spark.sql.catalog.Database;
-import org.apache.spark.sql.catalog.Function;
-import org.apache.spark.sql.catalog.Table;
import org.apache.spark.sql.catalyst.InternalRow;
import org.apache.spark.sql.sources.v2.ContinuousReadSupport;
import org.apache.spark.sql.sources.v2.DataSourceOptions;
@@ -48,21 +39,18 @@ import
org.apache.spark.sql.sources.v2.reader.InputPartitionReader;
import org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader;
import org.apache.spark.sql.sources.v2.reader.streaming.Offset;
import org.apache.spark.sql.types.StructType;
-import org.apache.spark.storage.StorageLevel;
-import scala.collection.immutable.Map;
/**
* This is a spark structured streaming {@link DataSourceV2} implementation.
As Continuous streaming
* is tagged experimental in spark, this class does no implement {@link
ContinuousReadSupport}.
*/
-public class DatasetSourceStreaming<T> implements DataSourceV2,
MicroBatchReadSupport{
+public class DatasetSourceStreaming<T> implements DataSourceV2,
MicroBatchReadSupport {
private int numPartitions;
private Long bundleSize;
private TranslationContext context;
private BoundedSource<T> source;
-
@Override
public MicroBatchReader createMicroBatchReader(
Optional<StructType> schema, String checkpointLocation,
DataSourceOptions options) {
@@ -157,7 +145,7 @@ public class DatasetSourceStreaming<T> implements
DataSourceV2, MicroBatchReadSu
}
}
- /** This class can be mapped to Beam {@link BoundedReader} */
+ /** This class can be mapped to Beam {@link BoundedReader}. */
private class DatasetMicroBatchPartitionReader implements
InputPartitionReader<InternalRow> {
BoundedReader<T> reader;
diff --git
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/ReadSourceTranslatorStreaming.java
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/ReadSourceTranslatorStreaming.java
index 6066822..8956ee9 100644
---
a/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/ReadSourceTranslatorStreaming.java
+++
b/runners/spark-structured-streaming/src/main/java/org/apache/beam/runners/spark/structuredstreaming/translation/streaming/ReadSourceTranslatorStreaming.java
@@ -21,8 +21,6 @@ import java.io.IOException;
import org.apache.beam.runners.core.construction.ReadTranslation;
import
org.apache.beam.runners.spark.structuredstreaming.translation.TransformTranslator;
import
org.apache.beam.runners.spark.structuredstreaming.translation.TranslationContext;
-import
org.apache.beam.runners.spark.structuredstreaming.translation.batch.DatasetSourceBatch;
-import org.apache.beam.sdk.io.BoundedSource;
import org.apache.beam.sdk.io.UnboundedSource;
import org.apache.beam.sdk.runners.AppliedPTransform;
import org.apache.beam.sdk.transforms.PTransform;
@@ -38,7 +36,8 @@ import org.apache.spark.sql.SparkSession;
class ReadSourceTranslatorStreaming<T>
implements TransformTranslator<PTransform<PBegin, PCollection<T>>> {
- private String SOURCE_PROVIDER_CLASS =
DatasetSourceStreaming.class.getCanonicalName();
+ private static final String SOURCE_PROVIDER_CLASS =
+ DatasetSourceStreaming.class.getCanonicalName();
@SuppressWarnings("unchecked")
@Override
@@ -50,8 +49,7 @@ class ReadSourceTranslatorStreaming<T>
UnboundedSource<T, UnboundedSource.CheckpointMark> source;
try {
- source = ReadTranslation
- .unboundedSourceFromTransform(rootTransform);
+ source = ReadTranslation.unboundedSourceFromTransform(rootTransform);
} catch (IOException e) {
throw new RuntimeException(e);
}
@@ -60,12 +58,14 @@ class ReadSourceTranslatorStreaming<T>
Dataset<Row> rowDataset =
sparkSession.readStream().format(SOURCE_PROVIDER_CLASS).load();
//TODO pass the source and the translation context serialized as string to
the DatasetSource
- MapFunction<Row, WindowedValue> func = new MapFunction<Row,
WindowedValue>() {
- @Override public WindowedValue call(Row value) throws Exception {
- //there is only one value put in each Row by the InputPartitionReader
- return value.<WindowedValue>getAs(0);
- }
- };
+ MapFunction<Row, WindowedValue> func =
+ new MapFunction<Row, WindowedValue>() {
+ @Override
+ public WindowedValue call(Row value) throws Exception {
+ //there is only one value put in each Row by the
InputPartitionReader
+ return value.<WindowedValue>getAs(0);
+ }
+ };
//TODO: is there a better way than using the raw WindowedValue? Can an
Encoder<WindowedVAlue<T>>
// be created ?
Dataset<WindowedValue> dataset = rowDataset.map(func,
Encoders.kryo(WindowedValue.class));
diff --git
a/runners/spark-structured-streaming/src/test/java/org/apache/beam/runners/spark/structuredstreaming/SourceTest.java
b/runners/spark-structured-streaming/src/test/java/org/apache/beam/runners/spark/structuredstreaming/SourceTest.java
index eea9769..662805c 100644
---
a/runners/spark-structured-streaming/src/test/java/org/apache/beam/runners/spark/structuredstreaming/SourceTest.java
+++
b/runners/spark-structured-streaming/src/test/java/org/apache/beam/runners/spark/structuredstreaming/SourceTest.java
@@ -1,3 +1,20 @@
+/*
+ * 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.structuredstreaming;
import org.apache.beam.sdk.Pipeline;
@@ -5,6 +22,7 @@ import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.transforms.Create;
+/** Source test of primitive pipeline. */
public class SourceTest {
public static void main(String[] args) {
PipelineOptions options = PipelineOptionsFactory.fromArgs(args).create();
@@ -12,5 +30,4 @@ public class SourceTest {
pipeline.apply(Create.of(1));
pipeline.run();
}
-
}
