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/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.mapreduce.lib.db;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.sql.Connection;
import java.sql.DatabaseMetaData;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Statement;
import java.sql.Types;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
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.MRJobConfig;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.util.ReflectionUtils;
import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.conf.Configurable;
import org.apache.hadoop.conf.Configuration;
/**
* A InputFormat that reads input data from an SQL table.
* Operates like DBInputFormat, but instead of using LIMIT and OFFSET to demarcate
* splits, it tries to generate WHERE clauses which separate the data into roughly
* equivalent shards.
*/
@InterfaceAudience.Public
@InterfaceStability.Evolving
public class DataDrivenDBInputFormat
extends DBInputFormat implements Configurable {
private static final Log LOG = LogFactory.getLog(DataDrivenDBInputFormat.class);
/** If users are providing their own query, the following string is expected to
appear in the WHERE clause, which will be substituted with a pair of conditions
on the input to allow input splits to parallelise the import. */
public static final String SUBSTITUTE_TOKEN = "$CONDITIONS";
/**
* A InputSplit that spans a set of rows
*/
@InterfaceStability.Evolving
public static class DataDrivenDBInputSplit extends DBInputFormat.DBInputSplit {
private String lowerBoundClause;
private String upperBoundClause;
/**
* Default Constructor
*/
public DataDrivenDBInputSplit() {
}
/**
* Convenience Constructor
* @param lower the string to be put in the WHERE clause to guard on the 'lower' end
* @param upper the string to be put in the WHERE clause to guard on the 'upper' end
*/
public DataDrivenDBInputSplit(final String lower, final String upper) {
this.lowerBoundClause = lower;
this.upperBoundClause = upper;
}
/**
* @return The total row count in this split
*/
public long getLength() throws IOException {
return 0; // unfortunately, we don't know this.
}
/** {@inheritDoc} */
public void readFields(DataInput input) throws IOException {
this.lowerBoundClause = Text.readString(input);
this.upperBoundClause = Text.readString(input);
}
/** {@inheritDoc} */
public void write(DataOutput output) throws IOException {
Text.writeString(output, this.lowerBoundClause);
Text.writeString(output, this.upperBoundClause);
}
public String getLowerClause() {
return lowerBoundClause;
}
public String getUpperClause() {
return upperBoundClause;
}
}
/**
* @return the DBSplitter implementation to use to divide the table/query into InputSplits.
*/
protected DBSplitter getSplitter(int sqlDataType) {
switch (sqlDataType) {
case Types.NUMERIC:
case Types.DECIMAL:
return new BigDecimalSplitter();
case Types.BIT:
case Types.BOOLEAN:
return new BooleanSplitter();
case Types.INTEGER:
case Types.TINYINT:
case Types.SMALLINT:
case Types.BIGINT:
return new IntegerSplitter();
case Types.REAL:
case Types.FLOAT:
case Types.DOUBLE:
return new FloatSplitter();
case Types.CHAR:
case Types.VARCHAR:
case Types.LONGVARCHAR:
return new TextSplitter();
case Types.DATE:
case Types.TIME:
case Types.TIMESTAMP:
return new DateSplitter();
default:
// TODO: Support BINARY, VARBINARY, LONGVARBINARY, DISTINCT, CLOB, BLOB, ARRAY
// STRUCT, REF, DATALINK, and JAVA_OBJECT.
return null;
}
}
/** {@inheritDoc} */
public List getSplits(JobContext job) throws IOException {
int targetNumTasks = job.getConfiguration().getInt(MRJobConfig.NUM_MAPS, 1);
if (1 == targetNumTasks) {
// There's no need to run a bounding vals query; just return a split
// that separates nothing. This can be considerably more optimal for a
// large table with no index.
List singletonSplit = new ArrayList();
singletonSplit.add(new DataDrivenDBInputSplit("1=1", "1=1"));
return singletonSplit;
}
ResultSet results = null;
Statement statement = null;
Connection connection = getConnection();
try {
statement = connection.createStatement();
results = statement.executeQuery(getBoundingValsQuery());
results.next();
// Based on the type of the results, use a different mechanism
// for interpolating split points (i.e., numeric splits, text splits,
// dates, etc.)
int sqlDataType = results.getMetaData().getColumnType(1);
DBSplitter splitter = getSplitter(sqlDataType);
if (null == splitter) {
throw new IOException("Unknown SQL data type: " + sqlDataType);
}
return splitter.split(job.getConfiguration(), results, getDBConf().getInputOrderBy());
} catch (SQLException e) {
throw new IOException(e.getMessage());
} finally {
// More-or-less ignore SQL exceptions here, but log in case we need it.
try {
if (null != results) {
results.close();
}
} catch (SQLException se) {
LOG.debug("SQLException closing resultset: " + se.toString());
}
try {
if (null != statement) {
statement.close();
}
} catch (SQLException se) {
LOG.debug("SQLException closing statement: " + se.toString());
}
try {
connection.commit();
closeConnection();
} catch (SQLException se) {
LOG.debug("SQLException committing split transaction: " + se.toString());
}
}
}
/**
* @return a query which returns the minimum and maximum values for
* the order-by column.
*
* The min value should be in the first column, and the
* max value should be in the second column of the results.
*/
protected String getBoundingValsQuery() {
// If the user has provided a query, use that instead.
String userQuery = getDBConf().getInputBoundingQuery();
if (null != userQuery) {
return userQuery;
}
// Auto-generate one based on the table name we've been provided with.
StringBuilder query = new StringBuilder();
String splitCol = getDBConf().getInputOrderBy();
query.append("SELECT MIN(").append(splitCol).append("), ");
query.append("MAX(").append(splitCol).append(") FROM ");
query.append(getDBConf().getInputTableName());
String conditions = getDBConf().getInputConditions();
if (null != conditions) {
query.append(" WHERE ( " + conditions + " )");
}
return query.toString();
}
/** Set the user-defined bounding query to use with a user-defined query.
This *must* include the substring "$CONDITIONS"
(DataDrivenDBInputFormat.SUBSTITUTE_TOKEN) inside the WHERE clause,
so that DataDrivenDBInputFormat knows where to insert split clauses.
e.g., "SELECT foo FROM mytable WHERE $CONDITIONS"
This will be expanded to something like:
SELECT foo FROM mytable WHERE (id > 100) AND (id < 250)
inside each split.
*/
public static void setBoundingQuery(Configuration conf, String query) {
if (null != query) {
// If the user's settng a query, warn if they don't allow conditions.
if (query.indexOf(SUBSTITUTE_TOKEN) == -1) {
LOG.warn("Could not find " + SUBSTITUTE_TOKEN + " token in query: " + query
+ "; splits may not partition data.");
}
}
conf.set(DBConfiguration.INPUT_BOUNDING_QUERY, query);
}
protected RecordReader createDBRecordReader(DBInputSplit split,
Configuration conf) throws IOException {
DBConfiguration dbConf = getDBConf();
@SuppressWarnings("unchecked")
Class inputClass = (Class) (dbConf.getInputClass());
String dbProductName = getDBProductName();
LOG.debug("Creating db record reader for db product: " + dbProductName);
try {
// use database product name to determine appropriate record reader.
if (dbProductName.startsWith("MYSQL")) {
// use MySQL-specific db reader.
return new MySQLDataDrivenDBRecordReader(split, inputClass,
conf, getConnection(), dbConf, dbConf.getInputConditions(),
dbConf.getInputFieldNames(), dbConf.getInputTableName());
} else {
// Generic reader.
return new DataDrivenDBRecordReader(split, inputClass,
conf, getConnection(), dbConf, dbConf.getInputConditions(),
dbConf.getInputFieldNames(), dbConf.getInputTableName(),
dbProductName);
}
} catch (SQLException ex) {
throw new IOException(ex.getMessage());
}
}
// Configuration methods override superclass to ensure that the proper
// DataDrivenDBInputFormat gets used.
/** Note that the "orderBy" column is called the "splitBy" in this version.
* We reuse the same field, but it's not strictly ordering it -- just partitioning
* the results.
*/
public static void setInput(Job job,
Class inputClass,
String tableName,String conditions,
String splitBy, String... fieldNames) {
DBInputFormat.setInput(job, inputClass, tableName, conditions, splitBy, fieldNames);
job.setInputFormatClass(DataDrivenDBInputFormat.class);
}
/** setInput() takes a custom query and a separate "bounding query" to use
instead of the custom "count query" used by DBInputFormat.
*/
public static void setInput(Job job,
Class inputClass,
String inputQuery, String inputBoundingQuery) {
DBInputFormat.setInput(job, inputClass, inputQuery, "");
job.getConfiguration().set(DBConfiguration.INPUT_BOUNDING_QUERY, inputBoundingQuery);
job.setInputFormatClass(DataDrivenDBInputFormat.class);
}
}
