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From md...@apache.org
Subject [04/11] ACCUMULO-1880 create mapreduce module
Date Mon, 21 Apr 2014 23:48:06 GMT
http://git-wip-us.apache.org/repos/asf/accumulo/blob/99baad37/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloOutputFormat.java
----------------------------------------------------------------------
diff --git a/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloOutputFormat.java b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloOutputFormat.java
new file mode 100644
index 0000000..af9bbae
--- /dev/null
+++ b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloOutputFormat.java
@@ -0,0 +1,545 @@
+/*
+ * 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.HashMap;
+import java.util.HashSet;
+import java.util.Map.Entry;
+import java.util.Set;
+
+import org.apache.accumulo.core.client.AccumuloException;
+import org.apache.accumulo.core.client.AccumuloSecurityException;
+import org.apache.accumulo.core.client.BatchWriter;
+import org.apache.accumulo.core.client.BatchWriterConfig;
+import org.apache.accumulo.core.client.ClientConfiguration;
+import org.apache.accumulo.core.client.Connector;
+import org.apache.accumulo.core.client.Instance;
+import org.apache.accumulo.core.client.MultiTableBatchWriter;
+import org.apache.accumulo.core.client.MutationsRejectedException;
+import org.apache.accumulo.core.client.TableExistsException;
+import org.apache.accumulo.core.client.TableNotFoundException;
+import org.apache.accumulo.core.client.ZooKeeperInstance;
+import org.apache.accumulo.core.client.mapreduce.lib.impl.OutputConfigurator;
+import org.apache.accumulo.core.client.mock.MockInstance;
+import org.apache.accumulo.core.client.security.SecurityErrorCode;
+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.ColumnUpdate;
+import org.apache.accumulo.core.data.KeyExtent;
+import org.apache.accumulo.core.data.Mutation;
+import org.apache.accumulo.core.security.ColumnVisibility;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.JobContext;
+import org.apache.hadoop.mapreduce.OutputCommitter;
+import org.apache.hadoop.mapreduce.OutputFormat;
+import org.apache.hadoop.mapreduce.RecordWriter;
+import org.apache.hadoop.mapreduce.TaskAttemptContext;
+import org.apache.hadoop.mapreduce.lib.output.NullOutputFormat;
+import org.apache.log4j.Level;
+import org.apache.log4j.Logger;
+
+/**
+ * This class allows MapReduce jobs to use Accumulo as the sink for data. This {@link OutputFormat} accepts keys and values of type {@link Text} (for a table
+ * name) and {@link Mutation} from the Map and Reduce functions.
+ * 
+ * The user must specify the following via static configurator methods:
+ * 
+ * <ul>
+ * <li>{@link AccumuloOutputFormat#setConnectorInfo(Job, String, AuthenticationToken)}
+ * <li>{@link AccumuloOutputFormat#setConnectorInfo(Job, String, String)}
+ * <li>{@link AccumuloOutputFormat#setZooKeeperInstance(Job, ClientConfiguration)} OR {@link AccumuloOutputFormat#setMockInstance(Job, String)}
+ * </ul>
+ * 
+ * Other static methods are optional.
+ */
+public class AccumuloOutputFormat extends OutputFormat<Text,Mutation> {
+
+  private static final Class<?> CLASS = AccumuloOutputFormat.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 if {@link #setCreateTables(Job, boolean)} is set to true)
+   * @param token
+   *          the user's password
+   * @since 1.5.0
+   */
+  public static void setConnectorInfo(Job job, String principal, AuthenticationToken token) throws AccumuloSecurityException {
+    OutputConfigurator.setConnectorInfo(CLASS, job.getConfiguration(), principal, token);
+  }
+
+  /**
+   * Sets the connector information needed to communicate with Accumulo in this job.
+   * 
+   * <p>
+   * Stores the password in a file in HDFS and pulls that into the Distributed Cache in an attempt to be more secure than storing it in the Configuration.
+   * 
+   * @param job
+   *          the Hadoop job instance to be configured
+   * @param principal
+   *          a valid Accumulo user name (user must have Table.CREATE permission if {@link #setCreateTables(Job, boolean)} is set to true)
+   * @param tokenFile
+   *          the path to the token file
+   * @since 1.6.0
+   */
+  public static void setConnectorInfo(Job job, String principal, String tokenFile) throws AccumuloSecurityException {
+    OutputConfigurator.setConnectorInfo(CLASS, job.getConfiguration(), principal, tokenFile);
+  }
+
+  /**
+   * Determines if the connector has been configured.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return true if the connector has been configured, false otherwise
+   * @since 1.5.0
+   * @see #setConnectorInfo(Job, String, AuthenticationToken)
+   */
+  protected static Boolean isConnectorInfoSet(JobContext context) {
+    return OutputConfigurator.isConnectorInfoSet(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * Gets the user name from the configuration.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return the user name
+   * @since 1.5.0
+   * @see #setConnectorInfo(Job, String, AuthenticationToken)
+   */
+  protected static String getPrincipal(JobContext context) {
+    return OutputConfigurator.getPrincipal(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * Gets the serialized token class from either the configuration or the token file.
+   * 
+   * @since 1.5.0
+   * @deprecated since 1.6.0; Use {@link #getAuthenticationToken(JobContext)} instead.
+   */
+  @Deprecated
+  protected static String getTokenClass(JobContext context) {
+    return getAuthenticationToken(context).getClass().getName();
+  }
+
+  /**
+   * Gets the serialized token from either the configuration or the token file.
+   * 
+   * @since 1.5.0
+   * @deprecated since 1.6.0; Use {@link #getAuthenticationToken(JobContext)} instead.
+   */
+  @Deprecated
+  protected static byte[] getToken(JobContext context) {
+    return AuthenticationTokenSerializer.serialize(getAuthenticationToken(context));
+  }
+
+  /**
+   * Gets the authenticated token from either the specified token file or directly from the configuration, whichever was used when the job was configured.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return the principal's authentication token
+   * @since 1.6.0
+   * @see #setConnectorInfo(Job, String, AuthenticationToken)
+   * @see #setConnectorInfo(Job, String, String)
+   */
+  protected static AuthenticationToken getAuthenticationToken(JobContext context) {
+    return OutputConfigurator.getAuthenticationToken(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * Configures a {@link ZooKeeperInstance} for this job.
+   * 
+   * @param job
+   *          the Hadoop job instance to be configured
+   * @param clientConfig
+   *          client configuration for specifying connection timeouts, SSL connection options, etc.
+   * @since 1.6.0
+   */
+  public static void setZooKeeperInstance(Job job, ClientConfiguration clientConfig) {
+    OutputConfigurator.setZooKeeperInstance(CLASS, job.getConfiguration(), clientConfig);
+  }
+
+  /**
+   * 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(Job job, String instanceName) {
+    OutputConfigurator.setMockInstance(CLASS, job.getConfiguration(), instanceName);
+  }
+
+  /**
+   * Initializes an Accumulo {@link Instance} based on the configuration.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return an Accumulo instance
+   * @since 1.5.0
+   * @see #setZooKeeperInstance(Job, ClientConfiguration)
+   * @see #setMockInstance(Job, String)
+   */
+  protected static Instance getInstance(JobContext context) {
+    return OutputConfigurator.getInstance(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * 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(Job job, Level level) {
+    OutputConfigurator.setLogLevel(CLASS, job.getConfiguration(), level);
+  }
+
+  /**
+   * Gets the log level from this configuration.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return the log level
+   * @since 1.5.0
+   * @see #setLogLevel(Job, Level)
+   */
+  protected static Level getLogLevel(JobContext context) {
+    return OutputConfigurator.getLogLevel(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * Sets the default table name to use if one emits a null in place of a table name for a given mutation. Table names can only be alpha-numeric and
+   * underscores.
+   * 
+   * @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 setDefaultTableName(Job job, String tableName) {
+    OutputConfigurator.setDefaultTableName(CLASS, job.getConfiguration(), tableName);
+  }
+
+  /**
+   * Gets the default table name from the configuration.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return the default table name
+   * @since 1.5.0
+   * @see #setDefaultTableName(Job, String)
+   */
+  protected static String getDefaultTableName(JobContext context) {
+    return OutputConfigurator.getDefaultTableName(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * Sets the configuration for for the job's {@link BatchWriter} instances. If not set, a new {@link BatchWriterConfig}, with sensible built-in defaults is
+   * used. Setting the configuration multiple times overwrites any previous configuration.
+   * 
+   * @param job
+   *          the Hadoop job instance to be configured
+   * @param bwConfig
+   *          the configuration for the {@link BatchWriter}
+   * @since 1.5.0
+   */
+  public static void setBatchWriterOptions(Job job, BatchWriterConfig bwConfig) {
+    OutputConfigurator.setBatchWriterOptions(CLASS, job.getConfiguration(), bwConfig);
+  }
+
+  /**
+   * Gets the {@link BatchWriterConfig} settings.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return the configuration object
+   * @since 1.5.0
+   * @see #setBatchWriterOptions(Job, BatchWriterConfig)
+   */
+  protected static BatchWriterConfig getBatchWriterOptions(JobContext context) {
+    return OutputConfigurator.getBatchWriterOptions(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * Sets the directive to create new tables, as necessary. Table names can only be alpha-numeric and underscores.
+   * 
+   * <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 setCreateTables(Job job, boolean enableFeature) {
+    OutputConfigurator.setCreateTables(CLASS, job.getConfiguration(), enableFeature);
+  }
+
+  /**
+   * Determines whether tables are permitted to be created as needed.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return true if the feature is disabled, false otherwise
+   * @since 1.5.0
+   * @see #setCreateTables(Job, boolean)
+   */
+  protected static Boolean canCreateTables(JobContext context) {
+    return OutputConfigurator.canCreateTables(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * Sets the directive to use simulation mode for this job. In simulation mode, no output is produced. This is useful for testing.
+   * 
+   * <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 setSimulationMode(Job job, boolean enableFeature) {
+    OutputConfigurator.setSimulationMode(CLASS, job.getConfiguration(), enableFeature);
+  }
+
+  /**
+   * Determines whether this feature is enabled.
+   * 
+   * @param context
+   *          the Hadoop context for the configured job
+   * @return true if the feature is enabled, false otherwise
+   * @since 1.5.0
+   * @see #setSimulationMode(Job, boolean)
+   */
+  protected static Boolean getSimulationMode(JobContext context) {
+    return OutputConfigurator.getSimulationMode(CLASS, InputFormatBase.getConfiguration(context));
+  }
+
+  /**
+   * A base class to be used to create {@link RecordWriter} instances that write to Accumulo.
+   */
+  protected static class AccumuloRecordWriter extends RecordWriter<Text,Mutation> {
+    private MultiTableBatchWriter mtbw = null;
+    private HashMap<Text,BatchWriter> bws = null;
+    private Text defaultTableName = null;
+
+    private boolean simulate = false;
+    private boolean createTables = false;
+
+    private long mutCount = 0;
+    private long valCount = 0;
+
+    private Connector conn;
+
+    protected AccumuloRecordWriter(TaskAttemptContext context) throws AccumuloException, AccumuloSecurityException, IOException {
+      Level l = getLogLevel(context);
+      if (l != null)
+        log.setLevel(getLogLevel(context));
+      this.simulate = getSimulationMode(context);
+      this.createTables = canCreateTables(context);
+
+      if (simulate)
+        log.info("Simulating output only. No writes to tables will occur");
+
+      this.bws = new HashMap<Text,BatchWriter>();
+
+      String tname = getDefaultTableName(context);
+      this.defaultTableName = (tname == null) ? null : new Text(tname);
+
+      if (!simulate) {
+        this.conn = getInstance(context).getConnector(getPrincipal(context), getAuthenticationToken(context));
+        mtbw = conn.createMultiTableBatchWriter(getBatchWriterOptions(context));
+      }
+    }
+
+    /**
+     * Push a mutation into a table. If table is null, the defaultTable will be used. If canCreateTable is set, the table will be created if it does not exist.
+     * The table name must only contain alphanumerics and underscore.
+     */
+    @Override
+    public void write(Text table, Mutation mutation) throws IOException {
+      if (table == null || table.toString().isEmpty())
+        table = this.defaultTableName;
+
+      if (!simulate && table == null)
+        throw new IOException("No table or default table specified. Try simulation mode next time");
+
+      ++mutCount;
+      valCount += mutation.size();
+      printMutation(table, mutation);
+
+      if (simulate)
+        return;
+
+      if (!bws.containsKey(table))
+        try {
+          addTable(table);
+        } catch (Exception e) {
+          e.printStackTrace();
+          throw new IOException(e);
+        }
+
+      try {
+        bws.get(table).addMutation(mutation);
+      } catch (MutationsRejectedException e) {
+        throw new IOException(e);
+      }
+    }
+
+    public void addTable(Text tableName) throws AccumuloException, AccumuloSecurityException {
+      if (simulate) {
+        log.info("Simulating adding table: " + tableName);
+        return;
+      }
+
+      log.debug("Adding table: " + tableName);
+      BatchWriter bw = null;
+      String table = tableName.toString();
+
+      if (createTables && !conn.tableOperations().exists(table)) {
+        try {
+          conn.tableOperations().create(table);
+        } catch (AccumuloSecurityException e) {
+          log.error("Accumulo security violation creating " + table, e);
+          throw e;
+        } catch (TableExistsException e) {
+          // Shouldn't happen
+        }
+      }
+
+      try {
+        bw = mtbw.getBatchWriter(table);
+      } catch (TableNotFoundException e) {
+        log.error("Accumulo table " + table + " doesn't exist and cannot be created.", e);
+        throw new AccumuloException(e);
+      } catch (AccumuloException e) {
+        throw e;
+      } catch (AccumuloSecurityException e) {
+        throw e;
+      }
+
+      if (bw != null)
+        bws.put(tableName, bw);
+    }
+
+    private int printMutation(Text table, Mutation m) {
+      if (log.isTraceEnabled()) {
+        log.trace(String.format("Table %s row key: %s", table, hexDump(m.getRow())));
+        for (ColumnUpdate cu : m.getUpdates()) {
+          log.trace(String.format("Table %s column: %s:%s", table, hexDump(cu.getColumnFamily()), hexDump(cu.getColumnQualifier())));
+          log.trace(String.format("Table %s security: %s", table, new ColumnVisibility(cu.getColumnVisibility()).toString()));
+          log.trace(String.format("Table %s value: %s", table, hexDump(cu.getValue())));
+        }
+      }
+      return m.getUpdates().size();
+    }
+
+    private String hexDump(byte[] ba) {
+      StringBuilder sb = new StringBuilder();
+      for (byte b : ba) {
+        if ((b > 0x20) && (b < 0x7e))
+          sb.append((char) b);
+        else
+          sb.append(String.format("x%02x", b));
+      }
+      return sb.toString();
+    }
+
+    @Override
+    public void close(TaskAttemptContext attempt) throws IOException, InterruptedException {
+      log.debug("mutations written: " + mutCount + ", values written: " + valCount);
+      if (simulate)
+        return;
+
+      try {
+        mtbw.close();
+      } catch (MutationsRejectedException e) {
+        if (e.getAuthorizationFailuresMap().size() >= 0) {
+          HashMap<String,Set<SecurityErrorCode>> tables = new HashMap<String,Set<SecurityErrorCode>>();
+          for (Entry<KeyExtent,Set<SecurityErrorCode>> ke : e.getAuthorizationFailuresMap().entrySet()) {
+            Set<SecurityErrorCode> secCodes = tables.get(ke.getKey().getTableId().toString());
+            if (secCodes == null) {
+              secCodes = new HashSet<SecurityErrorCode>();
+              tables.put(ke.getKey().getTableId().toString(), secCodes);
+            }
+            secCodes.addAll(ke.getValue());
+          }
+
+          log.error("Not authorized to write to tables : " + tables);
+        }
+
+        if (e.getConstraintViolationSummaries().size() > 0) {
+          log.error("Constraint violations : " + e.getConstraintViolationSummaries().size());
+        }
+      }
+    }
+  }
+
+  @Override
+  public void checkOutputSpecs(JobContext job) throws IOException {
+    if (!isConnectorInfoSet(job))
+      throw new IOException("Connector info has not been set.");
+    try {
+      // if the instance isn't configured, it will complain here
+      String principal = getPrincipal(job);
+      AuthenticationToken token = getAuthenticationToken(job);
+      Connector c = getInstance(job).getConnector(principal, token);
+      if (!c.securityOperations().authenticateUser(principal, token))
+        throw new IOException("Unable to authenticate user");
+    } catch (AccumuloException e) {
+      throw new IOException(e);
+    } catch (AccumuloSecurityException e) {
+      throw new IOException(e);
+    }
+  }
+
+  @Override
+  public OutputCommitter getOutputCommitter(TaskAttemptContext context) {
+    return new NullOutputFormat<Text,Mutation>().getOutputCommitter(context);
+  }
+
+  @Override
+  public RecordWriter<Text,Mutation> getRecordWriter(TaskAttemptContext attempt) throws IOException {
+    try {
+      return new AccumuloRecordWriter(attempt);
+    } catch (Exception e) {
+      throw new IOException(e);
+    }
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/accumulo/blob/99baad37/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloRowInputFormat.java
----------------------------------------------------------------------
diff --git a/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloRowInputFormat.java b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloRowInputFormat.java
new file mode 100644
index 0000000..37caf15
--- /dev/null
+++ b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/AccumuloRowInputFormat.java
@@ -0,0 +1,79 @@
+/*
+ * 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.Map.Entry;
+
+import org.apache.accumulo.core.client.ClientConfiguration;
+import org.apache.accumulo.core.client.RowIterator;
+import org.apache.accumulo.core.client.security.tokens.AuthenticationToken;
+import org.apache.accumulo.core.data.Key;
+import org.apache.accumulo.core.data.Value;
+import org.apache.accumulo.core.security.Authorizations;
+import org.apache.accumulo.core.util.PeekingIterator;
+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.RecordReader;
+import org.apache.hadoop.mapreduce.TaskAttemptContext;
+
+/**
+ * This class allows MapReduce jobs to use Accumulo as the source of data. This {@link InputFormat} provides row names as {@link Text} as keys, and a
+ * corresponding {@link PeekingIterator} as a value, which in turn makes the {@link Key}/{@link Value} pairs for that row available to the Map function.
+ * 
+ * The user must specify the following via static configurator methods:
+ * 
+ * <ul>
+ * <li>{@link AccumuloRowInputFormat#setConnectorInfo(Job, String, AuthenticationToken)}
+ * <li>{@link AccumuloRowInputFormat#setInputTableName(Job, String)}
+ * <li>{@link AccumuloRowInputFormat#setScanAuthorizations(Job, Authorizations)}
+ * <li>{@link AccumuloRowInputFormat#setZooKeeperInstance(Job, ClientConfiguration)} OR {@link AccumuloRowInputFormat#setMockInstance(Job, String)}
+ * </ul>
+ * 
+ * Other static methods are optional.
+ */
+public class AccumuloRowInputFormat extends InputFormatBase<Text,PeekingIterator<Entry<Key,Value>>> {
+  @Override
+  public RecordReader<Text,PeekingIterator<Entry<Key,Value>>> createRecordReader(InputSplit split, TaskAttemptContext context) throws IOException,
+      InterruptedException {
+    log.setLevel(getLogLevel(context));
+    return new RecordReaderBase<Text,PeekingIterator<Entry<Key,Value>>>() {
+      RowIterator rowIterator;
+
+      @Override
+      public void initialize(InputSplit inSplit, TaskAttemptContext attempt) throws IOException {
+        super.initialize(inSplit, attempt);
+        rowIterator = new RowIterator(scannerIterator);
+        currentK = new Text();
+        currentV = null;
+      }
+
+      @Override
+      public boolean nextKeyValue() throws IOException, InterruptedException {
+        if (!rowIterator.hasNext())
+          return false;
+        currentV = new PeekingIterator<Entry<Key,Value>>(rowIterator.next());
+        numKeysRead = rowIterator.getKVCount();
+        currentKey = currentV.peek().getKey();
+        currentK = new Text(currentKey.getRow());
+        return true;
+      }
+    };
+  }
+}

http://git-wip-us.apache.org/repos/asf/accumulo/blob/99baad37/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/InputFormatBase.java
----------------------------------------------------------------------
diff --git a/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/InputFormatBase.java b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/InputFormatBase.java
new file mode 100644
index 0000000..e58e350
--- /dev/null
+++ b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/InputFormatBase.java
@@ -0,0 +1,384 @@
+/*
+ * 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/99baad37/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/InputTableConfig.java
----------------------------------------------------------------------
diff --git a/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/InputTableConfig.java b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/InputTableConfig.java
new file mode 100644
index 0000000..e59451e
--- /dev/null
+++ b/mapreduce/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/99baad37/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/RangeInputSplit.java
----------------------------------------------------------------------
diff --git a/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/RangeInputSplit.java b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/RangeInputSplit.java
new file mode 100644
index 0000000..4b5a149
--- /dev/null
+++ b/mapreduce/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/99baad37/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/ConfiguratorBase.java
----------------------------------------------------------------------
diff --git a/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/ConfiguratorBase.java b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/ConfiguratorBase.java
new file mode 100644
index 0000000..4610556
--- /dev/null
+++ b/mapreduce/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/99baad37/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/DistributedCacheHelper.java
----------------------------------------------------------------------
diff --git a/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/DistributedCacheHelper.java b/mapreduce/src/main/java/org/apache/accumulo/core/client/mapreduce/lib/impl/DistributedCacheHelper.java
new file mode 100644
index 0000000..c694b9a
--- /dev/null
+++ b/mapreduce/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);
+  }
+}


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