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Posted to commits@accumulo.apache.org by ct...@apache.org on 2013/12/03 22:16:44 UTC
[08/10] git commit: Merge branch '1.4.5-SNAPSHOT' into 1.5.1-SNAPSHOT
Merge branch '1.4.5-SNAPSHOT' into 1.5.1-SNAPSHOT
Project: http://git-wip-us.apache.org/repos/asf/accumulo/repo
Commit: http://git-wip-us.apache.org/repos/asf/accumulo/commit/cccdb8cb
Tree: http://git-wip-us.apache.org/repos/asf/accumulo/tree/cccdb8cb
Diff: http://git-wip-us.apache.org/repos/asf/accumulo/diff/cccdb8cb
Branch: refs/heads/1.6.0-SNAPSHOT
Commit: cccdb8cb4d4645df25e07e96d7ecac333b316348
Parents: 39260cb a3a8895
Author: Christopher Tubbs <ct...@apache.org>
Authored: Tue Dec 3 15:30:01 2013 -0500
Committer: Christopher Tubbs <ct...@apache.org>
Committed: Tue Dec 3 15:30:01 2013 -0500
----------------------------------------------------------------------
.../core/client/mapred/InputFormatBase.java | 185 ++++++------
.../core/client/mapreduce/InputFormatBase.java | 282 +++++++++----------
.../core/client/mapreduce/RangeInputSplit.java | 72 ++---
.../mapreduce/AccumuloInputFormatTest.java | 22 +-
.../apache/accumulo/server/util/Initialize.java | 116 ++++----
.../tabletserver/log/MultiReaderTest.java | 33 ++-
.../accumulo/server/util/InitializeTest.java | 11 +-
7 files changed, 363 insertions(+), 358 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/accumulo/blob/cccdb8cb/core/src/main/java/org/apache/accumulo/core/client/mapred/InputFormatBase.java
----------------------------------------------------------------------
diff --cc core/src/main/java/org/apache/accumulo/core/client/mapred/InputFormatBase.java
index 0be4706,0000000..fe75453
mode 100644,000000..100644
--- a/core/src/main/java/org/apache/accumulo/core/client/mapred/InputFormatBase.java
+++ b/core/src/main/java/org/apache/accumulo/core/client/mapred/InputFormatBase.java
@@@ -1,913 -1,0 +1,910 @@@
+/*
+ * 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.mapred;
+
+import java.io.IOException;
+import java.net.InetAddress;
+import java.nio.ByteBuffer;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.Map.Entry;
+import java.util.Set;
+
+import org.apache.accumulo.core.Constants;
+import org.apache.accumulo.core.client.AccumuloException;
+import org.apache.accumulo.core.client.AccumuloSecurityException;
+import org.apache.accumulo.core.client.ClientSideIteratorScanner;
+import org.apache.accumulo.core.client.Connector;
+import org.apache.accumulo.core.client.Instance;
+import org.apache.accumulo.core.client.IsolatedScanner;
+import org.apache.accumulo.core.client.IteratorSetting;
+import org.apache.accumulo.core.client.RowIterator;
+import org.apache.accumulo.core.client.Scanner;
+import org.apache.accumulo.core.client.TableDeletedException;
+import org.apache.accumulo.core.client.TableNotFoundException;
+import org.apache.accumulo.core.client.TableOfflineException;
+import org.apache.accumulo.core.client.ZooKeeperInstance;
+import org.apache.accumulo.core.client.impl.OfflineScanner;
+import org.apache.accumulo.core.client.impl.Tables;
+import org.apache.accumulo.core.client.impl.TabletLocator;
- import org.apache.accumulo.core.client.mapred.RangeInputSplit;
+import org.apache.accumulo.core.client.mapreduce.lib.util.InputConfigurator;
+import org.apache.accumulo.core.client.mock.MockInstance;
+import org.apache.accumulo.core.client.security.tokens.AuthenticationToken;
+import org.apache.accumulo.core.data.Key;
+import org.apache.accumulo.core.data.KeyExtent;
+import org.apache.accumulo.core.data.PartialKey;
+import org.apache.accumulo.core.data.Range;
+import org.apache.accumulo.core.data.Value;
+import org.apache.accumulo.core.master.state.tables.TableState;
+import org.apache.accumulo.core.security.Authorizations;
+import org.apache.accumulo.core.security.CredentialHelper;
+import org.apache.accumulo.core.security.thrift.TCredentials;
+import org.apache.accumulo.core.util.Pair;
+import org.apache.accumulo.core.util.UtilWaitThread;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.mapred.InputFormat;
+import org.apache.hadoop.mapred.InputSplit;
+import org.apache.hadoop.mapred.JobConf;
+import org.apache.hadoop.mapred.RecordReader;
+import org.apache.hadoop.mapred.Reporter;
+import org.apache.log4j.Level;
+import org.apache.log4j.Logger;
+
+/**
+ * This abstract {@link InputFormat} class allows MapReduce jobs to use Accumulo as the source of K,V pairs.
+ * <p>
+ * Subclasses must implement a {@link #getRecordReader(InputSplit, JobConf, Reporter)} 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#next(Object, Object)} to transform them to the desired generic types K,V.
+ * <p>
+ * See {@link AccumuloInputFormat} for an example implementation.
+ */
+public abstract class InputFormatBase<K,V> implements InputFormat<K,V> {
-
++
+ private static final Class<?> CLASS = AccumuloInputFormat.class;
+ protected static final Logger log = Logger.getLogger(CLASS);
-
++
+ /**
+ * 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 job
+ * the Hadoop job instance to be configured
+ * @param principal
+ * a valid Accumulo user name (user must have Table.CREATE permission)
+ * @param token
+ * the user's password
+ * @throws AccumuloSecurityException
+ * @since 1.5.0
+ */
+ public static void setConnectorInfo(JobConf job, String principal, AuthenticationToken token) throws AccumuloSecurityException {
+ InputConfigurator.setConnectorInfo(CLASS, job, principal, token);
+ }
-
++
+ /**
+ * Determines if the connector has been configured.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return true if the connector has been configured, false otherwise
+ * @since 1.5.0
+ * @see #setConnectorInfo(JobConf, String, AuthenticationToken)
+ */
+ protected static Boolean isConnectorInfoSet(JobConf job) {
+ return InputConfigurator.isConnectorInfoSet(CLASS, job);
+ }
-
++
+ /**
+ * Gets the user name from the configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return the user name
+ * @since 1.5.0
+ * @see #setConnectorInfo(JobConf, String, AuthenticationToken)
+ */
+ protected static String getPrincipal(JobConf job) {
+ return InputConfigurator.getPrincipal(CLASS, job);
+ }
-
++
+ /**
+ * Gets the serialized token class from the configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return the user name
+ * @since 1.5.0
+ * @see #setConnectorInfo(JobConf, String, AuthenticationToken)
+ */
+ protected static String getTokenClass(JobConf job) {
+ return InputConfigurator.getTokenClass(CLASS, job);
+ }
-
++
+ /**
+ * Gets the password from the configuration. WARNING: The password 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 job
+ * the Hadoop context for the configured job
+ * @return the decoded user password
+ * @since 1.5.0
+ * @see #setConnectorInfo(JobConf, String, AuthenticationToken)
+ */
+ protected static byte[] getToken(JobConf job) {
+ return InputConfigurator.getToken(CLASS, job);
+ }
-
++
+ /**
+ * Configures a {@link ZooKeeperInstance} for this job.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param instanceName
+ * the Accumulo instance name
+ * @param zooKeepers
+ * a comma-separated list of zookeeper servers
+ * @since 1.5.0
+ */
+ public static void setZooKeeperInstance(JobConf job, String instanceName, String zooKeepers) {
+ InputConfigurator.setZooKeeperInstance(CLASS, job, instanceName, zooKeepers);
+ }
-
++
+ /**
+ * Configures a {@link MockInstance} for this job.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param instanceName
+ * the Accumulo instance name
+ * @since 1.5.0
+ */
+ public static void setMockInstance(JobConf job, String instanceName) {
+ InputConfigurator.setMockInstance(CLASS, job, instanceName);
+ }
-
++
+ /**
+ * Initializes an Accumulo {@link Instance} based on the configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return an Accumulo instance
+ * @since 1.5.0
+ * @see #setZooKeeperInstance(JobConf, String, String)
+ * @see #setMockInstance(JobConf, String)
+ */
+ protected static Instance getInstance(JobConf job) {
+ return InputConfigurator.getInstance(CLASS, job);
+ }
-
++
+ /**
+ * Sets the log level for this job.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param level
+ * the logging level
+ * @since 1.5.0
+ */
+ public static void setLogLevel(JobConf job, Level level) {
+ InputConfigurator.setLogLevel(CLASS, job, level);
+ }
-
++
+ /**
+ * Gets the log level from this configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return the log level
+ * @since 1.5.0
+ * @see #setLogLevel(JobConf, Level)
+ */
+ protected static Level getLogLevel(JobConf job) {
+ return InputConfigurator.getLogLevel(CLASS, job);
+ }
-
++
+ /**
+ * 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(JobConf job, String tableName) {
+ InputConfigurator.setInputTableName(CLASS, job, tableName);
+ }
-
++
+ /**
+ * Gets the table name from the configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return the table name
+ * @since 1.5.0
+ * @see #setInputTableName(JobConf, String)
+ */
+ protected static String getInputTableName(JobConf job) {
+ return InputConfigurator.getInputTableName(CLASS, job);
+ }
-
++
+ /**
+ * Sets the {@link Authorizations} used to scan. Must be a subset of the user's authorization. Defaults to the empty set.
+ *
+ * @param job
+ * the Hadoop job instance to be configured
+ * @param auths
+ * the user's authorizations
+ * @since 1.5.0
+ */
+ public static void setScanAuthorizations(JobConf job, Authorizations auths) {
+ InputConfigurator.setScanAuthorizations(CLASS, job, auths);
+ }
-
++
+ /**
+ * Gets the authorizations to set for the scans from the configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return the Accumulo scan authorizations
+ * @since 1.5.0
+ * @see #setScanAuthorizations(JobConf, Authorizations)
+ */
+ protected static Authorizations getScanAuthorizations(JobConf job) {
+ return InputConfigurator.getScanAuthorizations(CLASS, job);
+ }
-
++
+ /**
+ * Sets the input ranges to scan for this job. If not set, the entire table will be scanned.
+ *
+ * @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(JobConf job, Collection<Range> ranges) {
+ InputConfigurator.setRanges(CLASS, job, ranges);
+ }
-
++
+ /**
+ * Gets the ranges to scan over from a job.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return the ranges
+ * @throws IOException
+ * if the ranges have been encoded improperly
+ * @since 1.5.0
+ * @see #setRanges(JobConf, Collection)
+ */
+ protected static List<Range> getRanges(JobConf job) throws IOException {
+ return InputConfigurator.getRanges(CLASS, job);
+ }
-
++
+ /**
+ * Restricts the columns that will be mapped over for this job.
+ *
+ * @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(JobConf job, Collection<Pair<Text,Text>> columnFamilyColumnQualifierPairs) {
+ InputConfigurator.fetchColumns(CLASS, job, columnFamilyColumnQualifierPairs);
+ }
-
++
+ /**
+ * Gets the columns to be mapped over from this job.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return a set of columns
+ * @since 1.5.0
+ * @see #fetchColumns(JobConf, Collection)
+ */
+ protected static Set<Pair<Text,Text>> getFetchedColumns(JobConf job) {
+ return InputConfigurator.getFetchedColumns(CLASS, job);
+ }
-
++
+ /**
+ * Encode an iterator on the input 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(JobConf job, IteratorSetting cfg) {
+ InputConfigurator.addIterator(CLASS, job, cfg);
+ }
-
++
+ /**
+ * Gets a list of the iterator settings (for iterators to apply to a scanner) from this configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return a list of iterators
+ * @since 1.5.0
+ * @see #addIterator(JobConf, IteratorSetting)
+ */
+ protected static List<IteratorSetting> getIterators(JobConf job) {
+ return InputConfigurator.getIterators(CLASS, job);
+ }
-
++
+ /**
+ * 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(JobConf, Collection)
+ * @since 1.5.0
+ */
+ public static void setAutoAdjustRanges(JobConf job, boolean enableFeature) {
+ InputConfigurator.setAutoAdjustRanges(CLASS, job, enableFeature);
+ }
-
++
+ /**
+ * Determines whether a configuration has auto-adjust ranges enabled.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return false if the feature is disabled, true otherwise
+ * @since 1.5.0
+ * @see #setAutoAdjustRanges(JobConf, boolean)
+ */
+ protected static boolean getAutoAdjustRanges(JobConf job) {
+ return InputConfigurator.getAutoAdjustRanges(CLASS, job);
+ }
-
++
+ /**
+ * 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(JobConf job, boolean enableFeature) {
+ InputConfigurator.setScanIsolation(CLASS, job, enableFeature);
+ }
-
++
+ /**
+ * Determines whether a configuration has isolation enabled.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.5.0
+ * @see #setScanIsolation(JobConf, boolean)
+ */
+ protected static boolean isIsolated(JobConf job) {
+ return InputConfigurator.isIsolated(CLASS, job);
+ }
-
++
+ /**
+ * 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(JobConf job, boolean enableFeature) {
+ InputConfigurator.setLocalIterators(CLASS, job, enableFeature);
+ }
-
++
+ /**
+ * Determines whether a configuration uses local iterators.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.5.0
+ * @see #setLocalIterators(JobConf, boolean)
+ */
+ protected static boolean usesLocalIterators(JobConf job) {
+ return InputConfigurator.usesLocalIterators(CLASS, job);
+ }
-
++
+ /**
+ * <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 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(JobConf job, boolean enableFeature) {
+ InputConfigurator.setOfflineTableScan(CLASS, job, enableFeature);
+ }
-
++
+ /**
+ * Determines whether a configuration has the offline table scan feature enabled.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return true if the feature is enabled, false otherwise
+ * @since 1.5.0
+ * @see #setOfflineTableScan(JobConf, boolean)
+ */
+ protected static boolean isOfflineScan(JobConf job) {
+ return InputConfigurator.isOfflineScan(CLASS, job);
+ }
-
++
+ /**
+ * Initializes an Accumulo {@link TabletLocator} based on the configuration.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @return an Accumulo tablet locator
+ * @throws TableNotFoundException
+ * if the table name set on the configuration doesn't exist
+ * @since 1.5.0
+ */
+ protected static TabletLocator getTabletLocator(JobConf job) throws TableNotFoundException {
+ return InputConfigurator.getTabletLocator(CLASS, job);
+ }
-
++
+ // InputFormat doesn't have the equivalent of OutputFormat's checkOutputSpecs(JobContext job)
+ /**
+ * Check whether a configuration is fully configured to be used with an Accumulo {@link org.apache.hadoop.mapreduce.InputFormat}.
+ *
+ * @param job
+ * the Hadoop context for the configured job
+ * @throws IOException
+ * if the context is improperly configured
+ * @since 1.5.0
+ */
+ protected static void validateOptions(JobConf job) throws IOException {
+ InputConfigurator.validateOptions(CLASS, job);
+ }
-
++
+ /**
+ * An abstract base class to be used to create {@link RecordReader} instances that convert from Accumulo {@link Key}/{@link Value} pairs to the user's K/V
+ * types.
+ *
+ * Subclasses must implement {@link #next(Object, Object)} to update key and value, and also to update the following variables:
+ * <ul>
+ * <li>Key {@link #currentKey} (used for progress reporting)</li>
+ * <li>int {@link #numKeysRead} (used for progress reporting)</li>
+ * </ul>
+ */
+ protected abstract static class RecordReaderBase<K,V> implements RecordReader<K,V> {
+ protected long numKeysRead;
+ protected Iterator<Entry<Key,Value>> scannerIterator;
+ protected RangeInputSplit split;
-
++
+ /**
+ * Apply the configured iterators from the configuration to the scanner.
+ *
- * @param job
- * the Hadoop context for the configured job
+ * @param scanner
+ * the scanner to configure
+ */
+ protected void setupIterators(List<IteratorSetting> iterators, Scanner scanner) {
+ for (IteratorSetting iterator : iterators) {
+ scanner.addScanIterator(iterator);
+ }
+ }
-
++
+ /**
+ * Initialize a scanner over the given input split using this task attempt configuration.
+ */
+ public void initialize(InputSplit inSplit, JobConf job) throws IOException {
+ Scanner scanner;
+ split = (RangeInputSplit) inSplit;
+ log.debug("Initializing input split: " + split.getRange());
+
+ Instance instance = split.getInstance();
+ if (null == instance) {
+ instance = getInstance(job);
+ }
+
+ String principal = split.getPrincipal();
+ if (null == principal) {
+ principal = getPrincipal(job);
+ }
+
+ AuthenticationToken token = split.getToken();
+ if (null == token) {
+ String tokenClass = getTokenClass(job);
+ byte[] tokenBytes = getToken(job);
+ try {
+ token = CredentialHelper.extractToken(tokenClass, tokenBytes);
+ } catch (AccumuloSecurityException e) {
+ throw new IOException(e);
+ }
+ }
+
+ Authorizations authorizations = split.getAuths();
+ if (null == authorizations) {
+ authorizations = getScanAuthorizations(job);
+ }
+
+ String table = split.getTable();
+ if (null == table) {
+ table = getInputTableName(job);
+ }
-
++
+ Boolean isOffline = split.isOffline();
+ if (null == isOffline) {
+ isOffline = isOfflineScan(job);
+ }
+
+ Boolean isIsolated = split.isIsolatedScan();
+ if (null == isIsolated) {
+ isIsolated = isIsolated(job);
+ }
+
+ Boolean usesLocalIterators = split.usesLocalIterators();
+ if (null == usesLocalIterators) {
+ usesLocalIterators = usesLocalIterators(job);
+ }
-
++
+ List<IteratorSetting> iterators = split.getIterators();
+ if (null == iterators) {
+ iterators = getIterators(job);
+ }
-
++
+ Set<Pair<Text,Text>> columns = split.getFetchedColumns();
+ if (null == columns) {
+ columns = getFetchedColumns(job);
+ }
-
++
+ try {
+ log.debug("Creating connector with user: " + principal);
+ Connector conn = instance.getConnector(principal, token);
+ log.debug("Creating scanner for table: " + table);
+ log.debug("Authorizations are: " + authorizations);
+ if (isOfflineScan(job)) {
+ String tokenClass = token.getClass().getCanonicalName();
+ ByteBuffer tokenBuffer = ByteBuffer.wrap(CredentialHelper.toBytes(token));
- scanner = new OfflineScanner(instance, new TCredentials(principal, tokenClass, tokenBuffer, instance.getInstanceID()), Tables.getTableId(
- instance, table), authorizations);
++ scanner = new OfflineScanner(instance, new TCredentials(principal, tokenClass, tokenBuffer, instance.getInstanceID()), Tables.getTableId(instance,
++ table), authorizations);
+ } else {
+ scanner = conn.createScanner(table, authorizations);
+ }
+ if (isIsolated) {
+ log.info("Creating isolated scanner");
+ scanner = new IsolatedScanner(scanner);
+ }
+ if (usesLocalIterators) {
+ log.info("Using local iterators");
+ scanner = new ClientSideIteratorScanner(scanner);
+ }
+ setupIterators(iterators, scanner);
+ } catch (Exception e) {
+ throw new IOException(e);
+ }
-
++
+ // setup a scanner within the bounds of this split
+ for (Pair<Text,Text> c : columns) {
+ if (c.getSecond() != null) {
+ log.debug("Fetching column " + c.getFirst() + ":" + c.getSecond());
+ scanner.fetchColumn(c.getFirst(), c.getSecond());
+ } else {
+ log.debug("Fetching column family " + c.getFirst());
+ scanner.fetchColumnFamily(c.getFirst());
+ }
+ }
-
++
+ scanner.setRange(split.getRange());
-
++
+ numKeysRead = 0;
-
++
+ // do this last after setting all scanner options
+ scannerIterator = scanner.iterator();
+ }
-
++
+ @Override
+ public void close() {}
-
++
+ @Override
+ public long getPos() throws IOException {
+ return numKeysRead;
+ }
-
++
+ @Override
+ public float getProgress() throws IOException {
+ if (numKeysRead > 0 && currentKey == null)
+ return 1.0f;
+ return split.getProgress(currentKey);
+ }
-
++
+ protected Key currentKey = null;
-
++
+ }
-
++
+ Map<String,Map<KeyExtent,List<Range>>> binOfflineTable(JobConf job, String tableName, List<Range> ranges) throws TableNotFoundException, AccumuloException,
+ AccumuloSecurityException {
-
++
+ Map<String,Map<KeyExtent,List<Range>>> binnedRanges = new HashMap<String,Map<KeyExtent,List<Range>>>();
-
++
+ Instance instance = getInstance(job);
+ Connector conn = instance.getConnector(getPrincipal(job), CredentialHelper.extractToken(getTokenClass(job), getToken(job)));
+ String tableId = Tables.getTableId(instance, tableName);
-
++
+ if (Tables.getTableState(instance, tableId) != TableState.OFFLINE) {
+ Tables.clearCache(instance);
+ if (Tables.getTableState(instance, tableId) != TableState.OFFLINE) {
+ throw new AccumuloException("Table is online " + tableName + "(" + tableId + ") cannot scan table in offline mode ");
+ }
+ }
-
++
+ for (Range range : ranges) {
+ Text startRow;
-
++
+ if (range.getStartKey() != null)
+ startRow = range.getStartKey().getRow();
+ else
+ startRow = new Text();
-
++
+ Range metadataRange = new Range(new KeyExtent(new Text(tableId), startRow, null).getMetadataEntry(), true, null, false);
+ Scanner scanner = conn.createScanner(Constants.METADATA_TABLE_NAME, Constants.NO_AUTHS);
+ Constants.METADATA_PREV_ROW_COLUMN.fetch(scanner);
+ scanner.fetchColumnFamily(Constants.METADATA_LAST_LOCATION_COLUMN_FAMILY);
+ scanner.fetchColumnFamily(Constants.METADATA_CURRENT_LOCATION_COLUMN_FAMILY);
+ scanner.fetchColumnFamily(Constants.METADATA_FUTURE_LOCATION_COLUMN_FAMILY);
+ scanner.setRange(metadataRange);
-
++
+ RowIterator rowIter = new RowIterator(scanner);
-
++
+ KeyExtent lastExtent = null;
-
++
+ while (rowIter.hasNext()) {
+ Iterator<Entry<Key,Value>> row = rowIter.next();
+ String last = "";
+ KeyExtent extent = null;
+ String location = null;
-
++
+ while (row.hasNext()) {
+ Entry<Key,Value> entry = row.next();
+ Key key = entry.getKey();
-
++
+ if (key.getColumnFamily().equals(Constants.METADATA_LAST_LOCATION_COLUMN_FAMILY)) {
+ last = entry.getValue().toString();
+ }
-
++
+ if (key.getColumnFamily().equals(Constants.METADATA_CURRENT_LOCATION_COLUMN_FAMILY)
+ || key.getColumnFamily().equals(Constants.METADATA_FUTURE_LOCATION_COLUMN_FAMILY)) {
+ location = entry.getValue().toString();
+ }
-
++
+ if (Constants.METADATA_PREV_ROW_COLUMN.hasColumns(key)) {
+ extent = new KeyExtent(key.getRow(), entry.getValue());
+ }
-
++
+ }
-
++
+ if (location != null)
+ return null;
-
++
+ if (!extent.getTableId().toString().equals(tableId)) {
+ throw new AccumuloException("Saw unexpected table Id " + tableId + " " + extent);
+ }
-
++
+ if (lastExtent != null && !extent.isPreviousExtent(lastExtent)) {
+ throw new AccumuloException(" " + lastExtent + " is not previous extent " + extent);
+ }
-
++
+ Map<KeyExtent,List<Range>> tabletRanges = binnedRanges.get(last);
+ if (tabletRanges == null) {
+ tabletRanges = new HashMap<KeyExtent,List<Range>>();
+ binnedRanges.put(last, tabletRanges);
+ }
-
++
+ List<Range> rangeList = tabletRanges.get(extent);
+ if (rangeList == null) {
+ rangeList = new ArrayList<Range>();
+ tabletRanges.put(extent, rangeList);
+ }
-
++
+ rangeList.add(range);
-
++
+ if (extent.getEndRow() == null || range.afterEndKey(new Key(extent.getEndRow()).followingKey(PartialKey.ROW))) {
+ break;
+ }
-
++
+ lastExtent = extent;
+ }
-
++
+ }
-
++
+ return binnedRanges;
+ }
-
++
+ /**
+ * Read the metadata table to get tablets and match up ranges to them.
+ */
+ @Override
+ public InputSplit[] getSplits(JobConf job, int numSplits) throws IOException {
+ Level logLevel = getLogLevel(job);
+ log.setLevel(logLevel);
-
++
+ validateOptions(job);
-
++
+ String tableName = getInputTableName(job);
+ boolean autoAdjust = getAutoAdjustRanges(job);
+ List<Range> ranges = autoAdjust ? Range.mergeOverlapping(getRanges(job)) : getRanges(job);
+ Instance instance = getInstance(job);
+ boolean offline = isOfflineScan(job);
+ boolean isolated = isIsolated(job);
+ boolean localIterators = usesLocalIterators(job);
+ boolean mockInstance = (null != instance && MockInstance.class.equals(instance.getClass()));
+ Set<Pair<Text,Text>> fetchedColumns = getFetchedColumns(job);
+ Authorizations auths = getScanAuthorizations(job);
+ String principal = getPrincipal(job);
+ String tokenClass = getTokenClass(job);
+ byte[] tokenBytes = getToken(job);
-
++
+ AuthenticationToken token;
+ try {
- token = CredentialHelper.extractToken(tokenClass, tokenBytes);
++ token = CredentialHelper.extractToken(tokenClass, tokenBytes);
+ } catch (AccumuloSecurityException e) {
+ throw new IOException(e);
+ }
-
++
+ List<IteratorSetting> iterators = getIterators(job);
-
++
+ if (ranges.isEmpty()) {
+ ranges = new ArrayList<Range>(1);
+ ranges.add(new Range());
+ }
-
++
+ // get the metadata information for these ranges
+ Map<String,Map<KeyExtent,List<Range>>> binnedRanges = new HashMap<String,Map<KeyExtent,List<Range>>>();
+ TabletLocator tl;
+ try {
+ if (isOfflineScan(job)) {
+ binnedRanges = binOfflineTable(job, tableName, ranges);
+ while (binnedRanges == null) {
+ // Some tablets were still online, try again
+ UtilWaitThread.sleep(100 + (int) (Math.random() * 100)); // sleep randomly between 100 and 200 ms
+ binnedRanges = binOfflineTable(job, tableName, ranges);
+ }
+ } else {
+ String tableId = null;
+ tl = getTabletLocator(job);
+ // its possible that the cache could contain complete, but old information about a tables tablets... so clear it
+ tl.invalidateCache();
+ while (!tl.binRanges(ranges, binnedRanges, new TCredentials(principal, tokenClass, ByteBuffer.wrap(tokenBytes), instance.getInstanceID())).isEmpty()) {
+ if (!(instance instanceof MockInstance)) {
+ if (tableId == null)
+ tableId = Tables.getTableId(instance, tableName);
+ if (!Tables.exists(instance, tableId))
+ throw new TableDeletedException(tableId);
+ if (Tables.getTableState(instance, tableId) == TableState.OFFLINE)
+ throw new TableOfflineException(instance, tableId);
+ }
+ binnedRanges.clear();
+ log.warn("Unable to locate bins for specified ranges. Retrying.");
+ UtilWaitThread.sleep(100 + (int) (Math.random() * 100)); // sleep randomly between 100 and 200 ms
+ tl.invalidateCache();
+ }
+ }
+ } catch (Exception e) {
+ throw new IOException(e);
+ }
-
++
+ ArrayList<RangeInputSplit> splits = new ArrayList<RangeInputSplit>(ranges.size());
+ HashMap<Range,ArrayList<String>> splitsToAdd = null;
-
++
+ if (!autoAdjust)
+ splitsToAdd = new HashMap<Range,ArrayList<String>>();
-
++
+ HashMap<String,String> hostNameCache = new HashMap<String,String>();
-
++
+ for (Entry<String,Map<KeyExtent,List<Range>>> tserverBin : binnedRanges.entrySet()) {
+ String ip = tserverBin.getKey().split(":", 2)[0];
+ String location = hostNameCache.get(ip);
+ if (location == null) {
+ InetAddress inetAddress = InetAddress.getByName(ip);
+ location = inetAddress.getHostName();
+ hostNameCache.put(ip, location);
+ }
-
++
+ for (Entry<KeyExtent,List<Range>> extentRanges : tserverBin.getValue().entrySet()) {
+ Range ke = extentRanges.getKey().toDataRange();
+ for (Range r : extentRanges.getValue()) {
+ if (autoAdjust) {
+ // divide ranges into smaller ranges, based on the tablets
+ splits.add(new RangeInputSplit(ke.clip(r), new String[] {location}));
+ } else {
+ // don't divide ranges
+ ArrayList<String> locations = splitsToAdd.get(r);
+ if (locations == null)
+ locations = new ArrayList<String>(1);
+ locations.add(location);
+ splitsToAdd.put(r, locations);
+ }
+ }
+ }
+ }
-
++
+ if (!autoAdjust)
+ for (Entry<Range,ArrayList<String>> entry : splitsToAdd.entrySet())
+ splits.add(new RangeInputSplit(entry.getKey(), entry.getValue().toArray(new String[0])));
-
++
+ for (RangeInputSplit split : splits) {
+ split.setTable(tableName);
+ split.setOffline(offline);
+ split.setIsolatedScan(isolated);
+ split.setUsesLocalIterators(localIterators);
+ split.setMockInstance(mockInstance);
+ split.setFetchedColumns(fetchedColumns);
+ split.setPrincipal(principal);
+ split.setToken(token);
+ split.setInstanceName(instance.getInstanceName());
+ split.setZooKeepers(instance.getZooKeepers());
+ split.setAuths(auths);
+ split.setIterators(iterators);
+ split.setLogLevel(logLevel);
+ }
-
++
+ return splits.toArray(new InputSplit[splits.size()]);
+ }
-
++
+}