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Posted to commits@accumulo.apache.org by ct...@apache.org on 2014/04/22 00:16:18 UTC
[09/11] Revert "ACCUMULO-1880 create mapreduce module"
http://git-wip-us.apache.org/repos/asf/accumulo/blob/a8577a1c/core/src/main/java/org/apache/accumulo/core/client/mapreduce/InputFormatBase.java
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diff --git a/core/src/main/java/org/apache/accumulo/core/client/mapreduce/InputFormatBase.java b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/InputFormatBase.java
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+/*
+ * 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.accumulo.core.client.mapreduce;
+
+import java.io.IOException;
+import java.util.Collection;
+import java.util.List;
+import java.util.Set;
+
+import org.apache.accumulo.core.client.ClientSideIteratorScanner;
+import org.apache.accumulo.core.client.IsolatedScanner;
+import org.apache.accumulo.core.client.IteratorSetting;
+import org.apache.accumulo.core.client.Scanner;
+import org.apache.accumulo.core.client.TableNotFoundException;
+import org.apache.accumulo.core.client.impl.TabletLocator;
+import org.apache.accumulo.core.client.mapreduce.lib.impl.InputConfigurator;
+import org.apache.accumulo.core.data.Key;
+import org.apache.accumulo.core.data.Range;
+import org.apache.accumulo.core.data.Value;
+import org.apache.accumulo.core.util.Pair;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.mapreduce.InputFormat;
+import org.apache.hadoop.mapreduce.InputSplit;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.JobContext;
+import org.apache.hadoop.mapreduce.RecordReader;
+import org.apache.hadoop.mapreduce.TaskAttemptContext;
+
+/**
+ * This abstract {@link InputFormat} class allows MapReduce jobs to use Accumulo as the source of K,V pairs.
+ * <p>
+ * Subclasses must implement a {@link #createRecordReader(InputSplit, TaskAttemptContext)} to provide a {@link RecordReader} for K,V.
+ * <p>
+ * A static base class, RecordReaderBase, is provided to retrieve Accumulo {@link Key}/{@link Value} pairs, but one must implement its
+ * {@link RecordReaderBase#nextKeyValue()} to transform them to the desired generic types K,V.
+ * <p>
+ * See {@link AccumuloInputFormat} for an example implementation.
+ */
+public abstract class InputFormatBase<K,V> extends AbstractInputFormat<K,V> {
+
+ /**
+ * Gets the table name from the configuration.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return the table name
+ * @since 1.5.0
+ * @see #setInputTableName(Job, String)
+ */
+ protected static String getInputTableName(JobContext context) {
+ return InputConfigurator.getInputTableName(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * Sets the name of the input table, over which this job will scan.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param tableName
+ * the table to use when the tablename is null in the write call
+ * @since 1.5.0
+ */
+ public static void setInputTableName(Job job, String tableName) {
+ InputConfigurator.setInputTableName(CLASS, job.getConfiguration(), tableName);
+ }
+
+ /**
+ * Sets the input ranges to scan for the single input table associated with this job.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param ranges
+ * the ranges that will be mapped over
+ * @since 1.5.0
+ */
+ public static void setRanges(Job job, Collection<Range> ranges) {
+ InputConfigurator.setRanges(CLASS, job.getConfiguration(), ranges);
+ }
+
+ /**
+ * Gets the ranges to scan over from a job.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return the ranges
+ * @since 1.5.0
+ * @see #setRanges(Job, Collection)
+ */
+ protected static List<Range> getRanges(JobContext context) throws IOException {
+ return InputConfigurator.getRanges(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * Restricts the columns that will be mapped over for this job for the default input table.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param columnFamilyColumnQualifierPairs
+ * a pair of {@link Text} objects corresponding to column family and column qualifier. If the column qualifier is null, the entire column family is
+ * selected. An empty set is the default and is equivalent to scanning the all columns.
+ * @since 1.5.0
+ */
+ public static void fetchColumns(Job job, Collection<Pair<Text,Text>> columnFamilyColumnQualifierPairs) {
+ InputConfigurator.fetchColumns(CLASS, job.getConfiguration(), columnFamilyColumnQualifierPairs);
+ }
+
+ /**
+ * Gets the columns to be mapped over from this job.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return a set of columns
+ * @since 1.5.0
+ * @see #fetchColumns(Job, Collection)
+ */
+ protected static Set<Pair<Text,Text>> getFetchedColumns(JobContext context) {
+ return InputConfigurator.getFetchedColumns(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * Encode an iterator on the single input table for this job.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param cfg
+ * the configuration of the iterator
+ * @since 1.5.0
+ */
+ public static void addIterator(Job job, IteratorSetting cfg) {
+ InputConfigurator.addIterator(CLASS, job.getConfiguration(), cfg);
+ }
+
+ /**
+ * Gets a list of the iterator settings (for iterators to apply to a scanner) from this configuration.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return a list of iterators
+ * @since 1.5.0
+ * @see #addIterator(Job, IteratorSetting)
+ */
+ protected static List<IteratorSetting> getIterators(JobContext context) {
+ return InputConfigurator.getIterators(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * Controls the automatic adjustment of ranges for this job. This feature merges overlapping ranges, then splits them to align with tablet boundaries.
+ * Disabling this feature will cause exactly one Map task to be created for each specified range. The default setting is enabled. *
+ *
+ * <p>
+ * By default, this feature is <b>enabled</b>.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param enableFeature
+ * the feature is enabled if true, disabled otherwise
+ * @see #setRanges(Job, Collection)
+ * @since 1.5.0
+ */
+ public static void setAutoAdjustRanges(Job job, boolean enableFeature) {
+ InputConfigurator.setAutoAdjustRanges(CLASS, job.getConfiguration(), enableFeature);
+ }
+
+ /**
+ * Determines whether a configuration has auto-adjust ranges enabled.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return false if the feature is disabled, true otherwise
+ * @since 1.5.0
+ * @see #setAutoAdjustRanges(Job, boolean)
+ */
+ protected static boolean getAutoAdjustRanges(JobContext context) {
+ return InputConfigurator.getAutoAdjustRanges(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * Controls the use of the {@link IsolatedScanner} in this job.
+ *
+ * <p>
+ * By default, this feature is <b>disabled</b>.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param enableFeature
+ * the feature is enabled if true, disabled otherwise
+ * @since 1.5.0
+ */
+ public static void setScanIsolation(Job job, boolean enableFeature) {
+ InputConfigurator.setScanIsolation(CLASS, job.getConfiguration(), enableFeature);
+ }
+
+ /**
+ * Determines whether a configuration has isolation enabled.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.5.0
+ * @see #setScanIsolation(Job, boolean)
+ */
+ protected static boolean isIsolated(JobContext context) {
+ return InputConfigurator.isIsolated(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * Controls the use of the {@link ClientSideIteratorScanner} in this job. Enabling this feature will cause the iterator stack to be constructed within the Map
+ * task, rather than within the Accumulo TServer. To use this feature, all classes needed for those iterators must be available on the classpath for the task.
+ *
+ * <p>
+ * By default, this feature is <b>disabled</b>.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param enableFeature
+ * the feature is enabled if true, disabled otherwise
+ * @since 1.5.0
+ */
+ public static void setLocalIterators(Job job, boolean enableFeature) {
+ InputConfigurator.setLocalIterators(CLASS, job.getConfiguration(), enableFeature);
+ }
+
+ /**
+ * Determines whether a configuration uses local iterators.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.5.0
+ * @see #setLocalIterators(Job, boolean)
+ */
+ protected static boolean usesLocalIterators(JobContext context) {
+ return InputConfigurator.usesLocalIterators(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * <p>
+ * Enable reading offline tables. By default, this feature is disabled and only online tables are scanned. This will make the map reduce job directly read the
+ * table's files. If the table is not offline, then the job will fail. If the table comes online during the map reduce job, it is likely that the job will
+ * fail.
+ *
+ * <p>
+ * To use this option, the map reduce user will need access to read the Accumulo directory in HDFS.
+ *
+ * <p>
+ * Reading the offline table will create the scan time iterator stack in the map process. So any iterators that are configured for the table will need to be
+ * on the mapper's classpath.
+ *
+ * <p>
+ * One way to use this feature is to clone a table, take the clone offline, and use the clone as the input table for a map reduce job. If you plan to map
+ * reduce over the data many times, it may be better to the compact the table, clone it, take it offline, and use the clone for all map reduce jobs. The
+ * reason to do this is that compaction will reduce each tablet in the table to one file, and it is faster to read from one file.
+ *
+ * <p>
+ * There are two possible advantages to reading a tables file directly out of HDFS. First, you may see better read performance. Second, it will support
+ * speculative execution better. When reading an online table speculative execution can put more load on an already slow tablet server.
+ *
+ * <p>
+ * By default, this feature is <b>disabled</b>.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param enableFeature
+ * the feature is enabled if true, disabled otherwise
+ * @since 1.5.0
+ */
+ public static void setOfflineTableScan(Job job, boolean enableFeature) {
+ InputConfigurator.setOfflineTableScan(CLASS, job.getConfiguration(), enableFeature);
+ }
+
+ /**
+ * Determines whether a configuration has the offline table scan feature enabled.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.5.0
+ * @see #setOfflineTableScan(Job, boolean)
+ */
+ protected static boolean isOfflineScan(JobContext context) {
+ return InputConfigurator.isOfflineScan(CLASS, getConfiguration(context));
+ }
+
+ /**
+ * Initializes an Accumulo {@link org.apache.accumulo.core.client.impl.TabletLocator} based on the configuration.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @return an Accumulo tablet locator
+ * @throws org.apache.accumulo.core.client.TableNotFoundException
+ * if the table name set on the configuration doesn't exist
+ * @since 1.5.0
+ * @deprecated since 1.6.0
+ */
+ @Deprecated
+ protected static TabletLocator getTabletLocator(JobContext context) throws TableNotFoundException {
+ return InputConfigurator.getTabletLocator(CLASS, getConfiguration(context), InputConfigurator.getInputTableName(CLASS, getConfiguration(context)));
+ }
+
+ protected abstract static class RecordReaderBase<K,V> extends AbstractRecordReader<K,V> {
+
+ /**
+ * Apply the configured iterators from the configuration to the scanner for the specified table name
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @param scanner
+ * the scanner to configure
+ * @since 1.6.0
+ */
+ @Override
+ protected void setupIterators(TaskAttemptContext context, Scanner scanner, String tableName, org.apache.accumulo.core.client.mapreduce.RangeInputSplit split) {
+ setupIterators(context, scanner, split);
+ }
+
+ /**
+ * Apply the configured iterators from the configuration to the scanner.
+ *
+ * @param context
+ * the Hadoop context for the configured job
+ * @param scanner
+ * the scanner to configure
+ */
+ @Deprecated
+ protected void setupIterators(TaskAttemptContext context, Scanner scanner) {
+ setupIterators(context, scanner, null);
+ }
+
+ /**
+ * Initialize a scanner over the given input split using this task attempt configuration.
+ */
+ protected void setupIterators(TaskAttemptContext context, Scanner scanner, org.apache.accumulo.core.client.mapreduce.RangeInputSplit split) {
+ List<IteratorSetting> iterators = null;
+ if (null == split) {
+ iterators = getIterators(context);
+ } else {
+ iterators = split.getIterators();
+ if (null == iterators) {
+ iterators = getIterators(context);
+ }
+ }
+ for (IteratorSetting iterator : iterators)
+ scanner.addScanIterator(iterator);
+ }
+ }
+
+ /**
+ * @deprecated since 1.5.2; Use {@link org.apache.accumulo.core.client.mapreduce.RangeInputSplit} instead.
+ * @see org.apache.accumulo.core.client.mapreduce.RangeInputSplit
+ */
+ @Deprecated
+ public static class RangeInputSplit extends org.apache.accumulo.core.client.mapreduce.RangeInputSplit {
+
+ public RangeInputSplit() {
+ super();
+ }
+
+ public RangeInputSplit(RangeInputSplit other) throws IOException {
+ super(other);
+ }
+
+ protected RangeInputSplit(String table, Range range, String[] locations) {
+ super(table, "", range, locations);
+ }
+
+ public RangeInputSplit(String table, String tableId, Range range, String[] locations) {
+ super(table, tableId, range, locations);
+ }
+ }
+}
http://git-wip-us.apache.org/repos/asf/accumulo/blob/a8577a1c/core/src/main/java/org/apache/accumulo/core/client/mapreduce/InputTableConfig.java
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diff --git a/core/src/main/java/org/apache/accumulo/core/client/mapreduce/InputTableConfig.java b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/InputTableConfig.java
new file mode 100644
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--- /dev/null
+++ b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/InputTableConfig.java
@@ -0,0 +1,367 @@
+/*
+ * 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.accumulo.core.client.mapreduce;
+
+import java.io.DataInput;
+import java.io.DataOutput;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.HashSet;
+import java.util.List;
+
+import org.apache.accumulo.core.client.IteratorSetting;
+import org.apache.accumulo.core.data.Range;
+import org.apache.accumulo.core.util.Pair;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.io.Writable;
+
+/**
+ * This class to holds a batch scan configuration for a table. It contains all the properties needed to specify how rows should be returned from the table.
+ */
+public class InputTableConfig implements Writable {
+
+ private List<IteratorSetting> iterators;
+ private List<Range> ranges;
+ private Collection<Pair<Text,Text>> columns;
+
+ private boolean autoAdjustRanges = true;
+ private boolean useLocalIterators = false;
+ private boolean useIsolatedScanners = false;
+ private boolean offlineScan = false;
+
+ public InputTableConfig() {}
+
+ /**
+ * Creates a batch scan config object out of a previously serialized batch scan config object.
+ *
+ * @param input
+ * the data input of the serialized batch scan config
+ */
+ public InputTableConfig(DataInput input) throws IOException {
+ readFields(input);
+ }
+
+ /**
+ * Sets the input ranges to scan for all tables associated with this job. This will be added to any per-table ranges that have been set using
+ *
+ * @param ranges
+ * the ranges that will be mapped over
+ * @since 1.6.0
+ */
+ public InputTableConfig setRanges(List<Range> ranges) {
+ this.ranges = ranges;
+ return this;
+ }
+
+ /**
+ * Returns the ranges to be queried in the configuration
+ */
+ public List<Range> getRanges() {
+ return ranges != null ? ranges : new ArrayList<Range>();
+ }
+
+ /**
+ * Restricts the columns that will be mapped over for this job for the default input table.
+ *
+ * @param columns
+ * a pair of {@link Text} objects corresponding to column family and column qualifier. If the column qualifier is null, the entire column family is
+ * selected. An empty set is the default and is equivalent to scanning the all columns.
+ * @since 1.6.0
+ */
+ public InputTableConfig fetchColumns(Collection<Pair<Text,Text>> columns) {
+ this.columns = columns;
+ return this;
+ }
+
+ /**
+ * Returns the columns to be fetched for this configuration
+ */
+ public Collection<Pair<Text,Text>> getFetchedColumns() {
+ return columns != null ? columns : new HashSet<Pair<Text,Text>>();
+ }
+
+ /**
+ * Set iterators on to be used in the query.
+ *
+ * @param iterators
+ * the configurations for the iterators
+ * @since 1.6.0
+ */
+ public InputTableConfig setIterators(List<IteratorSetting> iterators) {
+ this.iterators = iterators;
+ return this;
+ }
+
+ /**
+ * Returns the iterators to be set on this configuration
+ */
+ public List<IteratorSetting> getIterators() {
+ return iterators != null ? iterators : new ArrayList<IteratorSetting>();
+ }
+
+ /**
+ * Controls the automatic adjustment of ranges for this job. This feature merges overlapping ranges, then splits them to align with tablet boundaries.
+ * Disabling this feature will cause exactly one Map task to be created for each specified range. The default setting is enabled. *
+ *
+ * <p>
+ * By default, this feature is <b>enabled</b>.
+ *
+ * @param autoAdjustRanges
+ * the feature is enabled if true, disabled otherwise
+ * @see #setRanges(java.util.List)
+ * @since 1.6.0
+ */
+ public InputTableConfig setAutoAdjustRanges(boolean autoAdjustRanges) {
+ this.autoAdjustRanges = autoAdjustRanges;
+ return this;
+ }
+
+ /**
+ * Determines whether a configuration has auto-adjust ranges enabled.
+ *
+ * @return false if the feature is disabled, true otherwise
+ * @since 1.6.0
+ * @see #setAutoAdjustRanges(boolean)
+ */
+ public boolean shouldAutoAdjustRanges() {
+ return autoAdjustRanges;
+ }
+
+ /**
+ * Controls the use of the {@link org.apache.accumulo.core.client.ClientSideIteratorScanner} in this job. Enabling this feature will cause the iterator stack
+ * to be constructed within the Map task, rather than within the Accumulo TServer. To use this feature, all classes needed for those iterators must be
+ * available on the classpath for the task.
+ *
+ * <p>
+ * By default, this feature is <b>disabled</b>.
+ *
+ * @param useLocalIterators
+ * the feature is enabled if true, disabled otherwise
+ * @since 1.6.0
+ */
+ public InputTableConfig setUseLocalIterators(boolean useLocalIterators) {
+ this.useLocalIterators = useLocalIterators;
+ return this;
+ }
+
+ /**
+ * Determines whether a configuration uses local iterators.
+ *
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.6.0
+ * @see #setUseLocalIterators(boolean)
+ */
+ public boolean shouldUseLocalIterators() {
+ return useLocalIterators;
+ }
+
+ /**
+ * <p>
+ * Enable reading offline tables. By default, this feature is disabled and only online tables are scanned. This will make the map reduce job directly read the
+ * table's files. If the table is not offline, then the job will fail. If the table comes online during the map reduce job, it is likely that the job will
+ * fail.
+ *
+ * <p>
+ * To use this option, the map reduce user will need access to read the Accumulo directory in HDFS.
+ *
+ * <p>
+ * Reading the offline table will create the scan time iterator stack in the map process. So any iterators that are configured for the table will need to be
+ * on the mapper's classpath. The accumulo-site.xml may need to be on the mapper's classpath if HDFS or the Accumulo directory in HDFS are non-standard.
+ *
+ * <p>
+ * One way to use this feature is to clone a table, take the clone offline, and use the clone as the input table for a map reduce job. If you plan to map
+ * reduce over the data many times, it may be better to the compact the table, clone it, take it offline, and use the clone for all map reduce jobs. The
+ * reason to do this is that compaction will reduce each tablet in the table to one file, and it is faster to read from one file.
+ *
+ * <p>
+ * There are two possible advantages to reading a tables file directly out of HDFS. First, you may see better read performance. Second, it will support
+ * speculative execution better. When reading an online table speculative execution can put more load on an already slow tablet server.
+ *
+ * <p>
+ * By default, this feature is <b>disabled</b>.
+ *
+ * @param offlineScan
+ * the feature is enabled if true, disabled otherwise
+ * @since 1.6.0
+ */
+ public InputTableConfig setOfflineScan(boolean offlineScan) {
+ this.offlineScan = offlineScan;
+ return this;
+ }
+
+ /**
+ * Determines whether a configuration has the offline table scan feature enabled.
+ *
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.6.0
+ * @see #setOfflineScan(boolean)
+ */
+ public boolean isOfflineScan() {
+ return offlineScan;
+ }
+
+ /**
+ * Controls the use of the {@link org.apache.accumulo.core.client.IsolatedScanner} in this job.
+ *
+ * <p>
+ * By default, this feature is <b>disabled</b>.
+ *
+ * @param useIsolatedScanners
+ * the feature is enabled if true, disabled otherwise
+ * @since 1.6.0
+ */
+ public InputTableConfig setUseIsolatedScanners(boolean useIsolatedScanners) {
+ this.useIsolatedScanners = useIsolatedScanners;
+ return this;
+ }
+
+ /**
+ * Determines whether a configuration has isolation enabled.
+ *
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.6.0
+ * @see #setUseIsolatedScanners(boolean)
+ */
+ public boolean shouldUseIsolatedScanners() {
+ return useIsolatedScanners;
+ }
+
+ /**
+ * Writes the state for the current object out to the specified {@link DataOutput}
+ *
+ * @param dataOutput
+ * the output for which to write the object's state
+ */
+ @Override
+ public void write(DataOutput dataOutput) throws IOException {
+ if (iterators != null) {
+ dataOutput.writeInt(iterators.size());
+ for (IteratorSetting setting : iterators)
+ setting.write(dataOutput);
+ } else {
+ dataOutput.writeInt(0);
+ }
+ if (ranges != null) {
+ dataOutput.writeInt(ranges.size());
+ for (Range range : ranges)
+ range.write(dataOutput);
+ } else {
+ dataOutput.writeInt(0);
+ }
+ if (columns != null) {
+ dataOutput.writeInt(columns.size());
+ for (Pair<Text,Text> column : columns) {
+ if (column.getSecond() == null) {
+ dataOutput.writeInt(1);
+ column.getFirst().write(dataOutput);
+ } else {
+ dataOutput.writeInt(2);
+ column.getFirst().write(dataOutput);
+ column.getSecond().write(dataOutput);
+ }
+ }
+ } else {
+ dataOutput.writeInt(0);
+ }
+ dataOutput.writeBoolean(autoAdjustRanges);
+ dataOutput.writeBoolean(useLocalIterators);
+ dataOutput.writeBoolean(useIsolatedScanners);
+ }
+
+ /**
+ * Reads the fields in the {@link DataInput} into the current object
+ *
+ * @param dataInput
+ * the input fields to read into the current object
+ */
+ @Override
+ public void readFields(DataInput dataInput) throws IOException {
+ // load iterators
+ long iterSize = dataInput.readInt();
+ if (iterSize > 0)
+ iterators = new ArrayList<IteratorSetting>();
+ for (int i = 0; i < iterSize; i++)
+ iterators.add(new IteratorSetting(dataInput));
+ // load ranges
+ long rangeSize = dataInput.readInt();
+ if (rangeSize > 0)
+ ranges = new ArrayList<Range>();
+ for (int i = 0; i < rangeSize; i++) {
+ Range range = new Range();
+ range.readFields(dataInput);
+ ranges.add(range);
+ }
+ // load columns
+ long columnSize = dataInput.readInt();
+ if (columnSize > 0)
+ columns = new HashSet<Pair<Text,Text>>();
+ for (int i = 0; i < columnSize; i++) {
+ long numPairs = dataInput.readInt();
+ Text colFam = new Text();
+ colFam.readFields(dataInput);
+ if (numPairs == 1) {
+ columns.add(new Pair<Text,Text>(colFam, null));
+ } else if (numPairs == 2) {
+ Text colQual = new Text();
+ colQual.readFields(dataInput);
+ columns.add(new Pair<Text,Text>(colFam, colQual));
+ }
+ }
+ autoAdjustRanges = dataInput.readBoolean();
+ useLocalIterators = dataInput.readBoolean();
+ useIsolatedScanners = dataInput.readBoolean();
+ }
+
+ @Override
+ public boolean equals(Object o) {
+ if (this == o)
+ return true;
+ if (o == null || getClass() != o.getClass())
+ return false;
+
+ InputTableConfig that = (InputTableConfig) o;
+
+ if (autoAdjustRanges != that.autoAdjustRanges)
+ return false;
+ if (offlineScan != that.offlineScan)
+ return false;
+ if (useIsolatedScanners != that.useIsolatedScanners)
+ return false;
+ if (useLocalIterators != that.useLocalIterators)
+ return false;
+ if (columns != null ? !columns.equals(that.columns) : that.columns != null)
+ return false;
+ if (iterators != null ? !iterators.equals(that.iterators) : that.iterators != null)
+ return false;
+ if (ranges != null ? !ranges.equals(that.ranges) : that.ranges != null)
+ return false;
+ return true;
+ }
+
+ @Override
+ public int hashCode() {
+ int result = 31 * (iterators != null ? iterators.hashCode() : 0);
+ result = 31 * result + (ranges != null ? ranges.hashCode() : 0);
+ result = 31 * result + (columns != null ? columns.hashCode() : 0);
+ result = 31 * result + (autoAdjustRanges ? 1 : 0);
+ result = 31 * result + (useLocalIterators ? 1 : 0);
+ result = 31 * result + (useIsolatedScanners ? 1 : 0);
+ result = 31 * result + (offlineScan ? 1 : 0);
+ return result;
+ }
+}
http://git-wip-us.apache.org/repos/asf/accumulo/blob/a8577a1c/core/src/main/java/org/apache/accumulo/core/client/mapreduce/RangeInputSplit.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/org/apache/accumulo/core/client/mapreduce/RangeInputSplit.java b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/RangeInputSplit.java
new file mode 100644
index 0000000..4b5a149
--- /dev/null
+++ b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/RangeInputSplit.java
@@ -0,0 +1,490 @@
+/*
+ * 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.accumulo.core.client.mapreduce;
+
+import java.io.DataInput;
+import java.io.DataOutput;
+import java.io.IOException;
+import java.math.BigInteger;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Set;
+
+import org.apache.accumulo.core.client.ClientConfiguration;
+import org.apache.accumulo.core.client.Instance;
+import org.apache.accumulo.core.client.IteratorSetting;
+import org.apache.accumulo.core.client.ZooKeeperInstance;
+import org.apache.accumulo.core.client.mapreduce.lib.impl.InputConfigurator;
+import org.apache.accumulo.core.client.mapreduce.lib.impl.ConfiguratorBase.TokenSource;
+import org.apache.accumulo.core.client.mock.MockInstance;
+import org.apache.accumulo.core.client.security.tokens.AuthenticationToken;
+import org.apache.accumulo.core.client.security.tokens.AuthenticationToken.AuthenticationTokenSerializer;
+import org.apache.accumulo.core.data.ByteSequence;
+import org.apache.accumulo.core.data.Key;
+import org.apache.accumulo.core.data.PartialKey;
+import org.apache.accumulo.core.data.Range;
+import org.apache.accumulo.core.security.Authorizations;
+import org.apache.accumulo.core.util.Pair;
+import org.apache.commons.codec.binary.Base64;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.io.Writable;
+import org.apache.hadoop.mapreduce.InputSplit;
+import org.apache.log4j.Level;
+
+/**
+ * The Class RangeInputSplit. Encapsulates an Accumulo range for use in Map Reduce jobs.
+ */
+public class RangeInputSplit extends InputSplit implements Writable {
+ private Range range;
+ private String[] locations;
+ private String tableId, tableName, instanceName, zooKeepers, principal;
+ private TokenSource tokenSource;
+ private String tokenFile;
+ private AuthenticationToken token;
+ private Boolean offline, mockInstance, isolatedScan, localIterators;
+ private Authorizations auths;
+ private Set<Pair<Text,Text>> fetchedColumns;
+ private List<IteratorSetting> iterators;
+ private Level level;
+
+ public RangeInputSplit() {
+ range = new Range();
+ locations = new String[0];
+ tableName = "";
+ tableId = "";
+ }
+
+ public RangeInputSplit(RangeInputSplit split) throws IOException {
+ this.setRange(split.getRange());
+ this.setLocations(split.getLocations());
+ this.setTableName(split.getTableName());
+ this.setTableId(split.getTableId());
+ }
+
+ protected RangeInputSplit(String table, String tableId, Range range, String[] locations) {
+ this.range = range;
+ setLocations(locations);
+ this.tableName = table;
+ this.tableId = tableId;
+ }
+
+ public Range getRange() {
+ return range;
+ }
+
+ private static byte[] extractBytes(ByteSequence seq, int numBytes) {
+ byte[] bytes = new byte[numBytes + 1];
+ bytes[0] = 0;
+ for (int i = 0; i < numBytes; i++) {
+ if (i >= seq.length())
+ bytes[i + 1] = 0;
+ else
+ bytes[i + 1] = seq.byteAt(i);
+ }
+ return bytes;
+ }
+
+ public static float getProgress(ByteSequence start, ByteSequence end, ByteSequence position) {
+ int maxDepth = Math.min(Math.max(end.length(), start.length()), position.length());
+ BigInteger startBI = new BigInteger(extractBytes(start, maxDepth));
+ BigInteger endBI = new BigInteger(extractBytes(end, maxDepth));
+ BigInteger positionBI = new BigInteger(extractBytes(position, maxDepth));
+ return (float) (positionBI.subtract(startBI).doubleValue() / endBI.subtract(startBI).doubleValue());
+ }
+
+ public float getProgress(Key currentKey) {
+ if (currentKey == null)
+ return 0f;
+ if (range.getStartKey() != null && range.getEndKey() != null) {
+ if (range.getStartKey().compareTo(range.getEndKey(), PartialKey.ROW) != 0) {
+ // just look at the row progress
+ return getProgress(range.getStartKey().getRowData(), range.getEndKey().getRowData(), currentKey.getRowData());
+ } else if (range.getStartKey().compareTo(range.getEndKey(), PartialKey.ROW_COLFAM) != 0) {
+ // just look at the column family progress
+ return getProgress(range.getStartKey().getColumnFamilyData(), range.getEndKey().getColumnFamilyData(), currentKey.getColumnFamilyData());
+ } else if (range.getStartKey().compareTo(range.getEndKey(), PartialKey.ROW_COLFAM_COLQUAL) != 0) {
+ // just look at the column qualifier progress
+ return getProgress(range.getStartKey().getColumnQualifierData(), range.getEndKey().getColumnQualifierData(), currentKey.getColumnQualifierData());
+ }
+ }
+ // if we can't figure it out, then claim no progress
+ return 0f;
+ }
+
+ /**
+ * This implementation of length is only an estimate, it does not provide exact values. Do not have your code rely on this return value.
+ */
+ @Override
+ public long getLength() throws IOException {
+ Text startRow = range.isInfiniteStartKey() ? new Text(new byte[] {Byte.MIN_VALUE}) : range.getStartKey().getRow();
+ Text stopRow = range.isInfiniteStopKey() ? new Text(new byte[] {Byte.MAX_VALUE}) : range.getEndKey().getRow();
+ int maxCommon = Math.min(7, Math.min(startRow.getLength(), stopRow.getLength()));
+ long diff = 0;
+
+ byte[] start = startRow.getBytes();
+ byte[] stop = stopRow.getBytes();
+ for (int i = 0; i < maxCommon; ++i) {
+ diff |= 0xff & (start[i] ^ stop[i]);
+ diff <<= Byte.SIZE;
+ }
+
+ if (startRow.getLength() != stopRow.getLength())
+ diff |= 0xff;
+
+ return diff + 1;
+ }
+
+ @Override
+ public String[] getLocations() throws IOException {
+ return Arrays.copyOf(locations, locations.length);
+ }
+
+ @Override
+ public void readFields(DataInput in) throws IOException {
+ range.readFields(in);
+ tableName = in.readUTF();
+ tableId = in.readUTF();
+ int numLocs = in.readInt();
+ locations = new String[numLocs];
+ for (int i = 0; i < numLocs; ++i)
+ locations[i] = in.readUTF();
+
+ if (in.readBoolean()) {
+ isolatedScan = in.readBoolean();
+ }
+
+ if (in.readBoolean()) {
+ offline = in.readBoolean();
+ }
+
+ if (in.readBoolean()) {
+ localIterators = in.readBoolean();
+ }
+
+ if (in.readBoolean()) {
+ mockInstance = in.readBoolean();
+ }
+
+ if (in.readBoolean()) {
+ int numColumns = in.readInt();
+ List<String> columns = new ArrayList<String>(numColumns);
+ for (int i = 0; i < numColumns; i++) {
+ columns.add(in.readUTF());
+ }
+
+ fetchedColumns = InputConfigurator.deserializeFetchedColumns(columns);
+ }
+
+ if (in.readBoolean()) {
+ String strAuths = in.readUTF();
+ auths = new Authorizations(strAuths.getBytes(StandardCharsets.UTF_8));
+ }
+
+ if (in.readBoolean()) {
+ principal = in.readUTF();
+ }
+
+ if (in.readBoolean()) {
+ int ordinal = in.readInt();
+ this.tokenSource = TokenSource.values()[ordinal];
+
+ switch (this.tokenSource) {
+ case INLINE:
+ String tokenClass = in.readUTF();
+ byte[] base64TokenBytes = in.readUTF().getBytes(StandardCharsets.UTF_8);
+ byte[] tokenBytes = Base64.decodeBase64(base64TokenBytes);
+
+ this.token = AuthenticationTokenSerializer.deserialize(tokenClass, tokenBytes);
+ break;
+
+ case FILE:
+ this.tokenFile = in.readUTF();
+
+ break;
+ default:
+ throw new IOException("Cannot parse unknown TokenSource ordinal");
+ }
+ }
+
+ if (in.readBoolean()) {
+ instanceName = in.readUTF();
+ }
+
+ if (in.readBoolean()) {
+ zooKeepers = in.readUTF();
+ }
+
+ if (in.readBoolean()) {
+ level = Level.toLevel(in.readInt());
+ }
+ }
+
+ @Override
+ public void write(DataOutput out) throws IOException {
+ range.write(out);
+ out.writeUTF(tableName);
+ out.writeUTF(tableId);
+ out.writeInt(locations.length);
+ for (int i = 0; i < locations.length; ++i)
+ out.writeUTF(locations[i]);
+
+ out.writeBoolean(null != isolatedScan);
+ if (null != isolatedScan) {
+ out.writeBoolean(isolatedScan);
+ }
+
+ out.writeBoolean(null != offline);
+ if (null != offline) {
+ out.writeBoolean(offline);
+ }
+
+ out.writeBoolean(null != localIterators);
+ if (null != localIterators) {
+ out.writeBoolean(localIterators);
+ }
+
+ out.writeBoolean(null != mockInstance);
+ if (null != mockInstance) {
+ out.writeBoolean(mockInstance);
+ }
+
+ out.writeBoolean(null != fetchedColumns);
+ if (null != fetchedColumns) {
+ String[] cols = InputConfigurator.serializeColumns(fetchedColumns);
+ out.writeInt(cols.length);
+ for (String col : cols) {
+ out.writeUTF(col);
+ }
+ }
+
+ out.writeBoolean(null != auths);
+ if (null != auths) {
+ out.writeUTF(auths.serialize());
+ }
+
+ out.writeBoolean(null != principal);
+ if (null != principal) {
+ out.writeUTF(principal);
+ }
+
+ out.writeBoolean(null != tokenSource);
+ if (null != tokenSource) {
+ out.writeInt(tokenSource.ordinal());
+
+ if (null != token && null != tokenFile) {
+ throw new IOException("Cannot use both inline AuthenticationToken and file-based AuthenticationToken");
+ } else if (null != token) {
+ out.writeUTF(token.getClass().getCanonicalName());
+ out.writeUTF(Base64.encodeBase64String(AuthenticationTokenSerializer.serialize(token)));
+ } else {
+ out.writeUTF(tokenFile);
+ }
+ }
+
+ out.writeBoolean(null != instanceName);
+ if (null != instanceName) {
+ out.writeUTF(instanceName);
+ }
+
+ out.writeBoolean(null != zooKeepers);
+ if (null != zooKeepers) {
+ out.writeUTF(zooKeepers);
+ }
+
+ out.writeBoolean(null != level);
+ if (null != level) {
+ out.writeInt(level.toInt());
+ }
+ }
+
+ @Override
+ public String toString() {
+ StringBuilder sb = new StringBuilder(256);
+ sb.append("Range: ").append(range);
+ sb.append(" Locations: ").append(Arrays.asList(locations));
+ sb.append(" Table: ").append(tableName);
+ sb.append(" TableID: ").append(tableId);
+ sb.append(" InstanceName: ").append(instanceName);
+ sb.append(" zooKeepers: ").append(zooKeepers);
+ sb.append(" principal: ").append(principal);
+ sb.append(" tokenSource: ").append(tokenSource);
+ sb.append(" authenticationToken: ").append(token);
+ sb.append(" authenticationTokenFile: ").append(tokenFile);
+ sb.append(" Authorizations: ").append(auths);
+ sb.append(" offlineScan: ").append(offline);
+ sb.append(" mockInstance: ").append(mockInstance);
+ sb.append(" isolatedScan: ").append(isolatedScan);
+ sb.append(" localIterators: ").append(localIterators);
+ sb.append(" fetchColumns: ").append(fetchedColumns);
+ sb.append(" iterators: ").append(iterators);
+ sb.append(" logLevel: ").append(level);
+ return sb.toString();
+ }
+
+ public String getTableName() {
+ return tableName;
+ }
+
+ public void setTableName(String table) {
+ this.tableName = table;
+ }
+
+ public void setTableId(String tableId) {
+ this.tableId = tableId;
+ }
+
+ public String getTableId() {
+ return tableId;
+ }
+
+ public Instance getInstance() {
+ if (null == instanceName) {
+ return null;
+ }
+
+ if (isMockInstance()) {
+ return new MockInstance(getInstanceName());
+ }
+
+ if (null == zooKeepers) {
+ return null;
+ }
+
+ return new ZooKeeperInstance(ClientConfiguration.loadDefault().withInstance(getInstanceName()).withZkHosts(getZooKeepers()));
+ }
+
+ public String getInstanceName() {
+ return instanceName;
+ }
+
+ public void setInstanceName(String instanceName) {
+ this.instanceName = instanceName;
+ }
+
+ public String getZooKeepers() {
+ return zooKeepers;
+ }
+
+ public void setZooKeepers(String zooKeepers) {
+ this.zooKeepers = zooKeepers;
+ }
+
+ public String getPrincipal() {
+ return principal;
+ }
+
+ public void setPrincipal(String principal) {
+ this.principal = principal;
+ }
+
+ public AuthenticationToken getToken() {
+ return token;
+ }
+
+ public void setToken(AuthenticationToken token) {
+ this.tokenSource = TokenSource.INLINE;
+ this.token = token;
+ }
+
+ public void setToken(String tokenFile) {
+ this.tokenSource = TokenSource.FILE;
+ this.tokenFile = tokenFile;
+ }
+
+ public Boolean isOffline() {
+ return offline;
+ }
+
+ public void setOffline(Boolean offline) {
+ this.offline = offline;
+ }
+
+ public void setLocations(String[] locations) {
+ this.locations = Arrays.copyOf(locations, locations.length);
+ }
+
+ public Boolean isMockInstance() {
+ return mockInstance;
+ }
+
+ public void setMockInstance(Boolean mockInstance) {
+ this.mockInstance = mockInstance;
+ }
+
+ public Boolean isIsolatedScan() {
+ return isolatedScan;
+ }
+
+ public void setIsolatedScan(Boolean isolatedScan) {
+ this.isolatedScan = isolatedScan;
+ }
+
+ public Authorizations getAuths() {
+ return auths;
+ }
+
+ public void setAuths(Authorizations auths) {
+ this.auths = auths;
+ }
+
+ public void setRange(Range range) {
+ this.range = range;
+ }
+
+ public Boolean usesLocalIterators() {
+ return localIterators;
+ }
+
+ public void setUsesLocalIterators(Boolean localIterators) {
+ this.localIterators = localIterators;
+ }
+
+ public Set<Pair<Text,Text>> getFetchedColumns() {
+ return fetchedColumns;
+ }
+
+ public void setFetchedColumns(Collection<Pair<Text,Text>> fetchedColumns) {
+ this.fetchedColumns = new HashSet<Pair<Text,Text>>();
+ for (Pair<Text,Text> columns : fetchedColumns) {
+ this.fetchedColumns.add(columns);
+ }
+ }
+
+ public void setFetchedColumns(Set<Pair<Text,Text>> fetchedColumns) {
+ this.fetchedColumns = fetchedColumns;
+ }
+
+ public List<IteratorSetting> getIterators() {
+ return iterators;
+ }
+
+ public void setIterators(List<IteratorSetting> iterators) {
+ this.iterators = iterators;
+ }
+
+ public Level getLogLevel() {
+ return level;
+ }
+
+ public void setLogLevel(Level level) {
+ this.level = level;
+ }
+}
http://git-wip-us.apache.org/repos/asf/accumulo/blob/a8577a1c/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/ConfiguratorBase.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/ConfiguratorBase.java b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/ConfiguratorBase.java
new file mode 100644
index 0000000..4610556
--- /dev/null
+++ b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/ConfiguratorBase.java
@@ -0,0 +1,369 @@
+/*
+ * 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.accumulo.core.client.mapreduce.lib.impl;
+
+import static com.google.common.base.Preconditions.checkArgument;
+
+import java.io.IOException;
+import java.net.URI;
+import java.net.URISyntaxException;
+import java.nio.charset.StandardCharsets;
+
+import org.apache.accumulo.core.client.AccumuloSecurityException;
+import org.apache.accumulo.core.client.ClientConfiguration;
+import org.apache.accumulo.core.client.Instance;
+import org.apache.accumulo.core.client.ZooKeeperInstance;
+import org.apache.accumulo.core.client.mock.MockInstance;
+import org.apache.accumulo.core.client.security.tokens.AuthenticationToken;
+import org.apache.accumulo.core.client.security.tokens.AuthenticationToken.AuthenticationTokenSerializer;
+import org.apache.accumulo.core.security.Credentials;
+import org.apache.commons.codec.binary.Base64;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FSDataInputStream;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.util.StringUtils;
+import org.apache.log4j.Level;
+import org.apache.log4j.Logger;
+
+/**
+ * @since 1.6.0
+ */
+public class ConfiguratorBase {
+
+ /**
+ * Configuration keys for {@link Instance#getConnector(String, AuthenticationToken)}.
+ *
+ * @since 1.6.0
+ */
+ public static enum ConnectorInfo {
+ IS_CONFIGURED, PRINCIPAL, TOKEN,
+ }
+
+ public static enum TokenSource {
+ FILE, INLINE;
+
+ private String prefix;
+
+ private TokenSource() {
+ prefix = name().toLowerCase() + ":";
+ }
+
+ public String prefix() {
+ return prefix;
+ }
+ }
+
+ /**
+ * Configuration keys for {@link Instance}, {@link ZooKeeperInstance}, and {@link MockInstance}.
+ *
+ * @since 1.6.0
+ */
+ public static enum InstanceOpts {
+ TYPE, NAME, ZOO_KEEPERS, CLIENT_CONFIG;
+ }
+
+ /**
+ * Configuration keys for general configuration options.
+ *
+ * @since 1.6.0
+ */
+ public static enum GeneralOpts {
+ LOG_LEVEL
+ }
+
+ /**
+ * Provides a configuration key for a given feature enum, prefixed by the implementingClass
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param e
+ * the enum used to provide the unique part of the configuration key
+ * @return the configuration key
+ * @since 1.6.0
+ */
+ protected static String enumToConfKey(Class<?> implementingClass, Enum<?> e) {
+ return implementingClass.getSimpleName() + "." + e.getDeclaringClass().getSimpleName() + "." + StringUtils.camelize(e.name().toLowerCase());
+ }
+
+ /**
+ * Sets the connector information needed to communicate with Accumulo in this job.
+ *
+ * <p>
+ * <b>WARNING:</b> The serialized token is stored in the configuration and shared with all MapReduce tasks. It is BASE64 encoded to provide a charset safe
+ * conversion to a string, and is not intended to be secure.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param principal
+ * a valid Accumulo user name
+ * @param token
+ * the user's password
+ * @since 1.6.0
+ */
+ public static void setConnectorInfo(Class<?> implementingClass, Configuration conf, String principal, AuthenticationToken token)
+ throws AccumuloSecurityException {
+ if (isConnectorInfoSet(implementingClass, conf))
+ throw new IllegalStateException("Connector info for " + implementingClass.getSimpleName() + " can only be set once per job");
+
+ checkArgument(principal != null, "principal is null");
+ checkArgument(token != null, "token is null");
+ conf.setBoolean(enumToConfKey(implementingClass, ConnectorInfo.IS_CONFIGURED), true);
+ conf.set(enumToConfKey(implementingClass, ConnectorInfo.PRINCIPAL), principal);
+ conf.set(enumToConfKey(implementingClass, ConnectorInfo.TOKEN),
+ TokenSource.INLINE.prefix() + token.getClass().getName() + ":" + Base64.encodeBase64String(AuthenticationTokenSerializer.serialize(token)));
+ }
+
+ /**
+ * Sets the connector information needed to communicate with Accumulo in this job.
+ *
+ * <p>
+ * Pulls a token file into the Distributed Cache that contains the authentication token in an attempt to be more secure than storing the password in the
+ * Configuration. Token file created with "bin/accumulo create-token".
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param principal
+ * a valid Accumulo user name
+ * @param tokenFile
+ * the path to the token file in DFS
+ * @since 1.6.0
+ */
+ public static void setConnectorInfo(Class<?> implementingClass, Configuration conf, String principal, String tokenFile) throws AccumuloSecurityException {
+ if (isConnectorInfoSet(implementingClass, conf))
+ throw new IllegalStateException("Connector info for " + implementingClass.getSimpleName() + " can only be set once per job");
+
+ checkArgument(principal != null, "principal is null");
+ checkArgument(tokenFile != null, "tokenFile is null");
+
+ try {
+ DistributedCacheHelper.addCacheFile(new URI(tokenFile), conf);
+ } catch (URISyntaxException e) {
+ throw new IllegalStateException("Unable to add tokenFile \"" + tokenFile + "\" to distributed cache.");
+ }
+
+ conf.setBoolean(enumToConfKey(implementingClass, ConnectorInfo.IS_CONFIGURED), true);
+ conf.set(enumToConfKey(implementingClass, ConnectorInfo.PRINCIPAL), principal);
+ conf.set(enumToConfKey(implementingClass, ConnectorInfo.TOKEN), TokenSource.FILE.prefix() + tokenFile);
+ }
+
+ /**
+ * Determines if the connector info has already been set for this instance.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @return true if the connector info has already been set, false otherwise
+ * @since 1.6.0
+ * @see #setConnectorInfo(Class, Configuration, String, AuthenticationToken)
+ */
+ public static Boolean isConnectorInfoSet(Class<?> implementingClass, Configuration conf) {
+ return conf.getBoolean(enumToConfKey(implementingClass, ConnectorInfo.IS_CONFIGURED), false);
+ }
+
+ /**
+ * Gets the user name from the configuration.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @return the principal
+ * @since 1.6.0
+ * @see #setConnectorInfo(Class, Configuration, String, AuthenticationToken)
+ */
+ public static String getPrincipal(Class<?> implementingClass, Configuration conf) {
+ return conf.get(enumToConfKey(implementingClass, ConnectorInfo.PRINCIPAL));
+ }
+
+ /**
+ * Gets the authenticated token from either the specified token file or directly from the configuration, whichever was used when the job was configured.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @return the principal's authentication token
+ * @since 1.6.0
+ * @see #setConnectorInfo(Class, Configuration, String, AuthenticationToken)
+ * @see #setConnectorInfo(Class, Configuration, String, String)
+ */
+ public static AuthenticationToken getAuthenticationToken(Class<?> implementingClass, Configuration conf) {
+ String token = conf.get(enumToConfKey(implementingClass, ConnectorInfo.TOKEN));
+ if (token == null || token.isEmpty())
+ return null;
+ if (token.startsWith(TokenSource.INLINE.prefix())) {
+ String[] args = token.substring(TokenSource.INLINE.prefix().length()).split(":", 2);
+ if (args.length == 2)
+ return AuthenticationTokenSerializer.deserialize(args[0], Base64.decodeBase64(args[1].getBytes(StandardCharsets.UTF_8)));
+ } else if (token.startsWith(TokenSource.FILE.prefix())) {
+ String tokenFileName = token.substring(TokenSource.FILE.prefix().length());
+ return getTokenFromFile(conf, getPrincipal(implementingClass, conf), tokenFileName);
+ }
+
+ throw new IllegalStateException("Token was not properly serialized into the configuration");
+ }
+
+ /**
+ * Reads from the token file in distributed cache. Currently, the token file stores data separated by colons e.g. principal:token_class:token
+ *
+ * @param conf
+ * the Hadoop context for the configured job
+ * @return path to the token file as a String
+ * @since 1.6.0
+ * @see #setConnectorInfo(Class, Configuration, String, AuthenticationToken)
+ */
+ public static AuthenticationToken getTokenFromFile(Configuration conf, String principal, String tokenFile) {
+ FSDataInputStream in = null;
+ try {
+ URI[] uris = DistributedCacheHelper.getCacheFiles(conf);
+ Path path = null;
+ for (URI u : uris) {
+ if (u.toString().equals(tokenFile)) {
+ path = new Path(u);
+ }
+ }
+ if (path == null) {
+ throw new IllegalArgumentException("Couldn't find password file called \"" + tokenFile + "\" in cache.");
+ }
+ FileSystem fs = FileSystem.get(conf);
+ in = fs.open(path);
+ } catch (IOException e) {
+ throw new IllegalArgumentException("Couldn't open password file called \"" + tokenFile + "\".");
+ }
+ try (java.util.Scanner fileScanner = new java.util.Scanner(in)) {
+ while (fileScanner.hasNextLine()) {
+ Credentials creds = Credentials.deserialize(fileScanner.nextLine());
+ if (principal.equals(creds.getPrincipal())) {
+ return creds.getToken();
+ }
+ }
+ throw new IllegalArgumentException("Couldn't find token for user \"" + principal + "\" in file \"" + tokenFile + "\"");
+ }
+ }
+
+ /**
+ * Configures a {@link ZooKeeperInstance} for this job.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param clientConfig
+ * client configuration for specifying connection timeouts, SSL connection options, etc.
+ * @since 1.6.0
+ */
+ public static void setZooKeeperInstance(Class<?> implementingClass, Configuration conf, ClientConfiguration clientConfig) {
+ String key = enumToConfKey(implementingClass, InstanceOpts.TYPE);
+ if (!conf.get(key, "").isEmpty())
+ throw new IllegalStateException("Instance info can only be set once per job; it has already been configured with " + conf.get(key));
+ conf.set(key, "ZooKeeperInstance");
+ if (clientConfig != null) {
+ conf.set(enumToConfKey(implementingClass, InstanceOpts.CLIENT_CONFIG), clientConfig.serialize());
+ }
+ }
+
+ /**
+ * Configures a {@link MockInstance} for this job.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param instanceName
+ * the Accumulo instance name
+ * @since 1.6.0
+ */
+ public static void setMockInstance(Class<?> implementingClass, Configuration conf, String instanceName) {
+ String key = enumToConfKey(implementingClass, InstanceOpts.TYPE);
+ if (!conf.get(key, "").isEmpty())
+ throw new IllegalStateException("Instance info can only be set once per job; it has already been configured with " + conf.get(key));
+ conf.set(key, "MockInstance");
+
+ checkArgument(instanceName != null, "instanceName is null");
+ conf.set(enumToConfKey(implementingClass, InstanceOpts.NAME), instanceName);
+ }
+
+ /**
+ * Initializes an Accumulo {@link Instance} based on the configuration.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @return an Accumulo instance
+ * @since 1.6.0
+ * @see #setZooKeeperInstance(Class, Configuration, ClientConfiguration)
+ * @see #setMockInstance(Class, Configuration, String)
+ */
+ public static Instance getInstance(Class<?> implementingClass, Configuration conf) {
+ String instanceType = conf.get(enumToConfKey(implementingClass, InstanceOpts.TYPE), "");
+ if ("MockInstance".equals(instanceType))
+ return new MockInstance(conf.get(enumToConfKey(implementingClass, InstanceOpts.NAME)));
+ else if ("ZooKeeperInstance".equals(instanceType)) {
+ String clientConfigString = conf.get(enumToConfKey(implementingClass, InstanceOpts.CLIENT_CONFIG));
+ if (clientConfigString == null) {
+ String instanceName = conf.get(enumToConfKey(implementingClass, InstanceOpts.NAME));
+ String zookeepers = conf.get(enumToConfKey(implementingClass, InstanceOpts.ZOO_KEEPERS));
+ return new ZooKeeperInstance(ClientConfiguration.loadDefault().withInstance(instanceName).withZkHosts(zookeepers));
+ } else {
+ return new ZooKeeperInstance(ClientConfiguration.deserialize(clientConfigString));
+ }
+ } else if (instanceType.isEmpty())
+ throw new IllegalStateException("Instance has not been configured for " + implementingClass.getSimpleName());
+ else
+ throw new IllegalStateException("Unrecognized instance type " + instanceType);
+ }
+
+ /**
+ * Sets the log level for this job.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param level
+ * the logging level
+ * @since 1.6.0
+ */
+ public static void setLogLevel(Class<?> implementingClass, Configuration conf, Level level) {
+ checkArgument(level != null, "level is null");
+ Logger.getLogger(implementingClass).setLevel(level);
+ conf.setInt(enumToConfKey(implementingClass, GeneralOpts.LOG_LEVEL), level.toInt());
+ }
+
+ /**
+ * Gets the log level from this configuration.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @return the log level
+ * @since 1.6.0
+ * @see #setLogLevel(Class, Configuration, Level)
+ */
+ public static Level getLogLevel(Class<?> implementingClass, Configuration conf) {
+ return Level.toLevel(conf.getInt(enumToConfKey(implementingClass, GeneralOpts.LOG_LEVEL), Level.INFO.toInt()));
+ }
+
+}
http://git-wip-us.apache.org/repos/asf/accumulo/blob/a8577a1c/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/DistributedCacheHelper.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/DistributedCacheHelper.java b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/DistributedCacheHelper.java
new file mode 100644
index 0000000..c694b9a
--- /dev/null
+++ b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/DistributedCacheHelper.java
@@ -0,0 +1,52 @@
+/*
+ * 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.accumulo.core.client.mapreduce.lib.impl;
+
+import java.io.IOException;
+import java.net.URI;
+
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.filecache.DistributedCache;
+import org.apache.hadoop.fs.Path;
+
+/**
+ * @since 1.6.0
+ */
+@SuppressWarnings("deprecation")
+public class DistributedCacheHelper {
+
+ /**
+ * @since 1.6.0
+ */
+ public static void addCacheFile(URI uri, Configuration conf) {
+ DistributedCache.addCacheFile(uri, conf);
+ }
+
+ /**
+ * @since 1.6.0
+ */
+ public static URI[] getCacheFiles(Configuration conf) throws IOException {
+ return DistributedCache.getCacheFiles(conf);
+ }
+
+ /**
+ * @since 1.6.0
+ */
+ public static Path[] getLocalCacheFiles(Configuration conf) throws IOException {
+ return DistributedCache.getLocalCacheFiles(conf);
+ }
+}
http://git-wip-us.apache.org/repos/asf/accumulo/blob/a8577a1c/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/FileOutputConfigurator.java
----------------------------------------------------------------------
diff --git a/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/FileOutputConfigurator.java b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/FileOutputConfigurator.java
new file mode 100644
index 0000000..ce84209
--- /dev/null
+++ b/core/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/FileOutputConfigurator.java
@@ -0,0 +1,187 @@
+/*
+ * 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.accumulo.core.client.mapreduce.lib.impl;
+
+import java.util.Arrays;
+import java.util.Map.Entry;
+
+import org.apache.accumulo.core.conf.AccumuloConfiguration;
+import org.apache.accumulo.core.conf.ConfigurationCopy;
+import org.apache.accumulo.core.conf.Property;
+import org.apache.hadoop.conf.Configuration;
+
+/**
+ * @since 1.6.0
+ */
+public class FileOutputConfigurator extends ConfiguratorBase {
+
+ /**
+ * Configuration keys for {@link AccumuloConfiguration}.
+ *
+ * @since 1.6.0
+ */
+ public static enum Opts {
+ ACCUMULO_PROPERTIES;
+ }
+
+ /**
+ * The supported Accumulo properties we set in this OutputFormat, that change the behavior of the RecordWriter.<br />
+ * These properties correspond to the supported public static setter methods available to this class.
+ *
+ * @param property
+ * the Accumulo property to check
+ * @since 1.6.0
+ */
+ protected static Boolean isSupportedAccumuloProperty(Property property) {
+ switch (property) {
+ case TABLE_FILE_COMPRESSION_TYPE:
+ case TABLE_FILE_COMPRESSED_BLOCK_SIZE:
+ case TABLE_FILE_BLOCK_SIZE:
+ case TABLE_FILE_COMPRESSED_BLOCK_SIZE_INDEX:
+ case TABLE_FILE_REPLICATION:
+ return true;
+ default:
+ return false;
+ }
+ }
+
+ /**
+ * Helper for transforming Accumulo configuration properties into something that can be stored safely inside the Hadoop Job configuration.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param property
+ * the supported Accumulo property
+ * @param value
+ * the value of the property to set
+ * @since 1.6.0
+ */
+ private static <T> void setAccumuloProperty(Class<?> implementingClass, Configuration conf, Property property, T value) {
+ if (isSupportedAccumuloProperty(property)) {
+ String val = String.valueOf(value);
+ if (property.getType().isValidFormat(val))
+ conf.set(enumToConfKey(implementingClass, Opts.ACCUMULO_PROPERTIES) + "." + property.getKey(), val);
+ else
+ throw new IllegalArgumentException("Value is not appropriate for property type '" + property.getType() + "'");
+ } else
+ throw new IllegalArgumentException("Unsupported configuration property " + property.getKey());
+ }
+
+ /**
+ * This helper method provides an AccumuloConfiguration object constructed from the Accumulo defaults, and overridden with Accumulo properties that have been
+ * stored in the Job's configuration.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @since 1.6.0
+ */
+ public static AccumuloConfiguration getAccumuloConfiguration(Class<?> implementingClass, Configuration conf) {
+ String prefix = enumToConfKey(implementingClass, Opts.ACCUMULO_PROPERTIES) + ".";
+ ConfigurationCopy acuConf = new ConfigurationCopy(AccumuloConfiguration.getDefaultConfiguration());
+ for (Entry<String,String> entry : conf)
+ if (entry.getKey().startsWith(prefix))
+ acuConf.set(Property.getPropertyByKey(entry.getKey().substring(prefix.length())), entry.getValue());
+ return acuConf;
+ }
+
+ /**
+ * Sets the compression type to use for data blocks. Specifying a compression may require additional libraries to be available to your Job.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param compressionType
+ * one of "none", "gz", "lzo", or "snappy"
+ * @since 1.6.0
+ */
+ public static void setCompressionType(Class<?> implementingClass, Configuration conf, String compressionType) {
+ if (compressionType == null || !Arrays.asList("none", "gz", "lzo", "snappy").contains(compressionType))
+ throw new IllegalArgumentException("Compression type must be one of: none, gz, lzo, snappy");
+ setAccumuloProperty(implementingClass, conf, Property.TABLE_FILE_COMPRESSION_TYPE, compressionType);
+ }
+
+ /**
+ * Sets the size for data blocks within each file.<br />
+ * Data blocks are a span of key/value pairs stored in the file that are compressed and indexed as a group.
+ *
+ * <p>
+ * Making this value smaller may increase seek performance, but at the cost of increasing the size of the indexes (which can also affect seek performance).
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param dataBlockSize
+ * the block size, in bytes
+ * @since 1.6.0
+ */
+ public static void setDataBlockSize(Class<?> implementingClass, Configuration conf, long dataBlockSize) {
+ setAccumuloProperty(implementingClass, conf, Property.TABLE_FILE_COMPRESSED_BLOCK_SIZE, dataBlockSize);
+ }
+
+ /**
+ * Sets the size for file blocks in the file system; file blocks are managed, and replicated, by the underlying file system.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param fileBlockSize
+ * the block size, in bytes
+ * @since 1.6.0
+ */
+ public static void setFileBlockSize(Class<?> implementingClass, Configuration conf, long fileBlockSize) {
+ setAccumuloProperty(implementingClass, conf, Property.TABLE_FILE_BLOCK_SIZE, fileBlockSize);
+ }
+
+ /**
+ * Sets the size for index blocks within each file; smaller blocks means a deeper index hierarchy within the file, while larger blocks mean a more shallow
+ * index hierarchy within the file. This can affect the performance of queries.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param indexBlockSize
+ * the block size, in bytes
+ * @since 1.6.0
+ */
+ public static void setIndexBlockSize(Class<?> implementingClass, Configuration conf, long indexBlockSize) {
+ setAccumuloProperty(implementingClass, conf, Property.TABLE_FILE_COMPRESSED_BLOCK_SIZE_INDEX, indexBlockSize);
+ }
+
+ /**
+ * Sets the file system replication factor for the resulting file, overriding the file system default.
+ *
+ * @param implementingClass
+ * the class whose name will be used as a prefix for the property configuration key
+ * @param conf
+ * the Hadoop configuration object to configure
+ * @param replication
+ * the number of replicas for produced files
+ * @since 1.6.0
+ */
+ public static void setReplication(Class<?> implementingClass, Configuration conf, int replication) {
+ setAccumuloProperty(implementingClass, conf, Property.TABLE_FILE_REPLICATION, replication);
+ }
+
+}