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https://issues.apache.org/jira/browse/BEAM-3912?focusedWorklogId=141144&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-141144
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ASF GitHub Bot logged work on BEAM-3912:
----------------------------------------
Author: ASF GitHub Bot
Created on: 05/Sep/18 08:13
Start Date: 05/Sep/18 08:13
Worklog Time Spent: 10m
Work Description: echauchot commented on a change in pull request #6306:
[BEAM-3912] Add HadoopOutputFormatIO support
URL: https://github.com/apache/beam/pull/6306#discussion_r215170317
##########
File path:
sdks/java/io/hadoop-output-format/src/main/java/org/apache/beam/sdk/io/hadoop/outputformat/HadoopOutputFormatIO.java
##########
@@ -0,0 +1,292 @@
+/*
+ * 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.sdk.io.hadoop.outputformat;
+
+import static com.google.common.base.Preconditions.checkArgument;
+
+import com.google.auto.value.AutoValue;
+import java.io.IOException;
+import java.lang.reflect.InvocationTargetException;
+import java.util.concurrent.ExecutionException;
+import javax.annotation.Nullable;
+import org.apache.beam.sdk.annotations.Experimental;
+import org.apache.beam.sdk.io.hadoop.SerializableConfiguration;
+import org.apache.beam.sdk.options.PipelineOptions;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.transforms.display.DisplayData;
+import org.apache.beam.sdk.values.KV;
+import org.apache.beam.sdk.values.PCollection;
+import org.apache.beam.sdk.values.PDone;
+import org.apache.beam.sdk.values.TypeDescriptor;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.mapreduce.JobID;
+import org.apache.hadoop.mapreduce.OutputCommitter;
+import org.apache.hadoop.mapreduce.OutputFormat;
+import org.apache.hadoop.mapreduce.RecordWriter;
+import org.apache.hadoop.mapreduce.TaskAttemptContext;
+import org.apache.hadoop.mapreduce.TaskAttemptID;
+import org.apache.hadoop.mapreduce.task.JobContextImpl;
+import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ * A {@link HadoopOutputFormatIO} is a Transform for writing data to any sink
which implements
+ * Hadoop {@link OutputFormat}. For example - Cassandra, Elasticsearch, HBase,
Redis, Postgres etc.
+ * {@link HadoopOutputFormatIO} has to make several performance trade-offs in
connecting to {@link
+ * OutputFormat}, so if there is another Beam IO Transform specifically for
connecting to your data
+ * sink of choice, we would recommend using that one, but this IO Transform
allows you to connect to
+ * many data sinks that do not yet have a Beam IO Transform.
+ *
+ * <p>You will need to pass a Hadoop {@link Configuration} with parameters
specifying how the write
+ * will occur. Many properties of the Configuration are optional, and some are
required for certain
+ * {@link OutputFormat} classes, but the following properties must be set for
all OutputFormats:
+ *
+ * <ul>
+ * <li>{@code mapreduce.job.outputformat.class}: The {@link OutputFormat}
class used to connect to
+ * your data sink of choice.
+ * <li>{@code mapreduce.job.outputformat.key.class}: The key class passed to
the {@link
+ * OutputFormat} in {@code mapreduce.job.outputformat.class}.
+ * <li>{@code mapreduce.job.outputformat.value.class}: The value class
passed to the {@link
+ * OutputFormat} in {@code mapreduce.job.outputformat.class}.
+ * </ul>
+ *
+ * For example:
+ *
+ * <pre>{@code
+ * Configuration myHadoopConfiguration = new Configuration(false);
+ * // Set Hadoop OutputFormat, key and value class in configuration
+ * myHadoopConfiguration.setClass("mapreduce.job.outputformat.class",
+ * MyDbOutputFormatClass, OutputFormat.class);
+ *
myHadoopConfiguration.setClass("mapreduce.job.outputformat.key.class",
+ * MyDbOutputFormatKeyClass, Object.class);
+ *
myHadoopConfiguration.setClass("mapreduce.job.outputformat.value.class",
+ * MyDbOutputFormatValueClass, Object.class);
+ * }</pre>
+ *
+ * <p>You will need to set appropriate OutputFormat key and value class (i.e.
+ * "mapreduce.job.outputformat.key.class" and
"mapreduce.job.outputformat.value.class") in Hadoop
+ * {@link Configuration}. If you set different OutputFormat key or value class
than OutputFormat's
+ * actual key or value class then, it may result in an error like "unexpected
extra bytes after
+ * decoding" while the decoding process of key/value object happens. Hence, it
is important to set
+ * appropriate OutputFormat key and value class.
+ *
+ * <h3>Writing using {@link HadoopOutputFormatIO}</h3>
+ *
+ * <pre>{@code
+ * Pipeline p = ...; // Create pipeline.
+ * // Read data only with Hadoop configuration.
+ * p.apply("read",
+ * HadoopOutputFormatIO.<OutputFormatKeyClass, OutputFormatKeyClass>write()
+ * .withConfiguration(myHadoopConfiguration);
+ * }</pre>
+ */
+@Experimental(Experimental.Kind.SOURCE_SINK)
+public class HadoopOutputFormatIO {
+ private static final Logger LOG =
LoggerFactory.getLogger(HadoopOutputFormatIO.class);
+
+ public static final String OUTPUTFORMAT_CLASS =
"mapreduce.job.outputformat.class";
+ public static final String OUTPUTFORMAT_KEY_CLASS =
"mapreduce.job.outputformat.key.class";
+ public static final String OUTPUTFORMAT_VALUE_CLASS =
"mapreduce.job.outputformat.value.class";
+
+ /**
+ * Creates an uninitialized {@link HadoopOutputFormatIO.Write}. Before use,
the {@code Write} must
+ * be initialized with a
HadoopOutputFormatIO.Write#withConfiguration(HadoopConfiguration) that
+ * specifies the sink.
+ */
+ public static <K, V> Write<K, V> write() {
+ return new AutoValue_HadoopOutputFormatIO_Write.Builder<K, V>().build();
+ }
+
+ /**
+ * A {@link PTransform} that writes to any data sink which implements Hadoop
OutputFormat. For
+ * e.g. Cassandra, Elasticsearch, HBase, Redis, Postgres, etc. See the
class-level Javadoc on
+ * {@link HadoopOutputFormatIO} for more information.
+ *
+ * @param <K> Type of keys to be written.
+ * @param <V> Type of values to be written.
+ * @see HadoopOutputFormatIO
+ */
+ @AutoValue
+ public abstract static class Write<K, V> extends
PTransform<PCollection<KV<K, V>>, PDone> {
+ // Returns the Hadoop Configuration which contains specification of sink.
+ @Nullable
+ public abstract SerializableConfiguration getConfiguration();
+
+ @Nullable
+ public abstract TypeDescriptor<?> getOutputFormatClass();
+
+ @Nullable
+ public abstract TypeDescriptor<?> getOutputFormatKeyClass();
+
+ @Nullable
+ public abstract TypeDescriptor<?> getOutputFormatValueClass();
+
+ abstract Builder<K, V> toBuilder();
+
+ @AutoValue.Builder
+ abstract static class Builder<K, V> {
+ abstract Builder<K, V> setConfiguration(SerializableConfiguration
configuration);
+
+ abstract Builder<K, V> setOutputFormatClass(TypeDescriptor<?>
outputFormatClass);
+
+ abstract Builder<K, V> setOutputFormatKeyClass(TypeDescriptor<?>
outputFormatKeyClass);
+
+ abstract Builder<K, V> setOutputFormatValueClass(TypeDescriptor<?>
outputFormatValueClass);
+
+ abstract Write<K, V> build();
+ }
+
+ /** Write to the sink using the options provided by the given
configuration. */
+ @SuppressWarnings("unchecked")
+ public Write<K, V> withConfiguration(Configuration configuration) {
+ validateConfiguration(configuration);
+ TypeDescriptor<?> outputFormatClass =
+ TypeDescriptor.of(configuration.getClass(OUTPUTFORMAT_CLASS, null));
+ TypeDescriptor<?> outputFormatKeyClass =
+ TypeDescriptor.of(configuration.getClass(OUTPUTFORMAT_KEY_CLASS,
null));
+ TypeDescriptor<?> outputFormatValueClass =
+ TypeDescriptor.of(configuration.getClass(OUTPUTFORMAT_VALUE_CLASS,
null));
+ Builder<K, V> builder =
+ toBuilder().setConfiguration(new
SerializableConfiguration(configuration));
+ builder.setOutputFormatClass(outputFormatClass);
+ builder.setOutputFormatKeyClass(outputFormatKeyClass);
+ builder.setOutputFormatValueClass(outputFormatValueClass);
+
+ return builder.build();
+ }
+
+ /**
+ * Validates that the mandatory configuration properties such as
OutputFormat class,
+ * OutputFormat key and value classes are provided in the Hadoop
configuration.
+ */
+ private void validateConfiguration(Configuration configuration) {
+ checkArgument(configuration != null, "Configuration can not be null");
+ checkArgument(
+ configuration.get(OUTPUTFORMAT_CLASS) != null,
+ "Configuration must contain \"" + OUTPUTFORMAT_CLASS + "\"");
+ checkArgument(
+ configuration.get(OUTPUTFORMAT_KEY_CLASS) != null,
+ "Configuration must contain \"" + OUTPUTFORMAT_KEY_CLASS + "\"");
+ checkArgument(
+ configuration.get(OUTPUTFORMAT_VALUE_CLASS) != null,
+ "Configuration must contain \"" + OUTPUTFORMAT_VALUE_CLASS + "\"");
+ }
+
+ @Override
+ public void validate(PipelineOptions pipelineOptions) {}
+
+ @Override
+ public void populateDisplayData(DisplayData.Builder builder) {
+ super.populateDisplayData(builder);
+ Configuration hadoopConfig = getConfiguration().get();
+ if (hadoopConfig != null) {
+ builder.addIfNotNull(
+ DisplayData.item(OUTPUTFORMAT_CLASS,
hadoopConfig.get(OUTPUTFORMAT_CLASS))
+ .withLabel("OutputFormat Class"));
+ builder.addIfNotNull(
+ DisplayData.item(OUTPUTFORMAT_KEY_CLASS,
hadoopConfig.get(OUTPUTFORMAT_KEY_CLASS))
+ .withLabel("OutputFormat Key Class"));
+ builder.addIfNotNull(
+ DisplayData.item(OUTPUTFORMAT_VALUE_CLASS,
hadoopConfig.get(OUTPUTFORMAT_VALUE_CLASS))
+ .withLabel("OutputFormat Value Class"));
+ }
+ }
+
+ @Override
+ public PDone expand(PCollection<KV<K, V>> input) {
+ input.apply(ParDo.of(new WriteFn<>(this)));
+ return PDone.in(input.getPipeline());
+ }
+ }
+
+ private static class WriteFn<K, V> extends DoFn<KV<K, V>, Void> {
Review comment:
This implementation writes record per record. Shouldn't it be batched (like
initializing batch in @StartBundle and writing it in @FinishBundle) ?
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Issue Time Tracking
-------------------
Worklog Id: (was: 141144)
Time Spent: 1h 50m (was: 1h 40m)
> Add support of HadoopOutputFormatIO
> -----------------------------------
>
> Key: BEAM-3912
> URL: https://issues.apache.org/jira/browse/BEAM-3912
> Project: Beam
> Issue Type: Improvement
> Components: io-java-hadoop
> Reporter: Alexey Romanenko
> Assignee: Alexey Romanenko
> Priority: Minor
> Time Spent: 1h 50m
> Remaining Estimate: 0h
>
> For the moment, there is only HadoopInputFormatIO in Beam. To provide a
> support of different writing IOs, that are not yet natively supported in Beam
> (for example, Apache Orc or HBase bulk load), it would make sense to add
> HadoopOutputFormatIO as well.
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