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Declarative Machine Learning
/*
* 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.sysml.api;
import java.util.Map;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.types.StructType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext;
import org.apache.sysml.runtime.instructions.spark.functions.GetMLBlock;
import org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils;
import org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtils;
import org.apache.sysml.runtime.matrix.MatrixCharacteristics;
import org.apache.sysml.runtime.matrix.data.CSVFileFormatProperties;
import org.apache.sysml.runtime.matrix.data.FrameBlock;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.data.MatrixIndexes;
/**
* This is a simple container object that returns the output of execute from MLContext
*
* @deprecated This will be removed in SystemML 1.0. Please migrate to {@link org.apache.sysml.api.mlcontext.MLContext}
* and {@link org.apache.sysml.api.mlcontext.MLResults}
*/
@Deprecated
public class MLOutput {
Map> _outputs;
private Map _outMetadata = null;
public MLOutput(Map> outputs, Map outMetadata) {
this._outputs = outputs;
this._outMetadata = outMetadata;
}
public MatrixBlock getMatrixBlock(String varName) throws DMLRuntimeException {
MatrixCharacteristics mc = getMatrixCharacteristics(varName);
// The matrix block is always pushed to an RDD and then we do collect
// We can later avoid this by returning symbol table rather than "Map> _outputs"
return SparkExecutionContext.toMatrixBlock(getBinaryBlockedRDD(varName), (int) mc.getRows(), (int) mc.getCols(),
mc.getRowsPerBlock(), mc.getColsPerBlock(), mc.getNonZeros());
}
@SuppressWarnings("unchecked")
public JavaPairRDD getBinaryBlockedRDD(String varName) throws DMLRuntimeException {
if(_outputs.containsKey(varName)) {
return (JavaPairRDD) _outputs.get(varName);
}
throw new DMLRuntimeException("Variable " + varName + " not found in the outputs.");
}
@SuppressWarnings("unchecked")
public JavaPairRDD getFrameBinaryBlockedRDD(String varName) throws DMLRuntimeException {
if(_outputs.containsKey(varName)) {
return (JavaPairRDD)_outputs.get(varName);
}
throw new DMLRuntimeException("Variable " + varName + " not found in the outputs.");
}
public MatrixCharacteristics getMatrixCharacteristics(String varName) throws DMLRuntimeException {
if(_outputs.containsKey(varName)) {
return _outMetadata.get(varName);
}
throw new DMLRuntimeException("Variable " + varName + " not found in the output symbol table.");
}
/**
* Note, the output DataFrame has an additional column ID.
* An easy way to get DataFrame without ID is by df.drop("__INDEX")
*
* @param sparkSession the Spark Session
* @param varName the variable name
* @return the DataFrame
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
public Dataset getDF(SparkSession sparkSession, String varName) throws DMLRuntimeException {
if(sparkSession == null) {
throw new DMLRuntimeException("SparkSession is not created.");
}
JavaPairRDD rdd = getBinaryBlockedRDD(varName);
if(rdd != null) {
MatrixCharacteristics mc = _outMetadata.get(varName);
return RDDConverterUtils.binaryBlockToDataFrame(sparkSession, rdd, mc, false);
}
throw new DMLRuntimeException("Variable " + varName + " not found in the output symbol table.");
}
/**
* Note, the output DataFrame has an additional column ID.
* An easy way to get DataFrame without ID is by df.drop("__INDEX")
*
* @param sqlContext the SQL Context
* @param varName the variable name
* @return the DataFrame
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
public Dataset getDF(SQLContext sqlContext, String varName) throws DMLRuntimeException {
if (sqlContext == null) {
throw new DMLRuntimeException("SQLContext is not created");
}
SparkSession sparkSession = sqlContext.sparkSession();
return getDF(sparkSession, varName);
}
/**
* Obtain the DataFrame
*
* @param sparkSession the Spark Session
* @param varName the variable name
* @param outputVector if true, returns DataFrame with two column: ID and org.apache.spark.ml.linalg.Vector
* @return the DataFrame
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
public Dataset getDF(SparkSession sparkSession, String varName, boolean outputVector) throws DMLRuntimeException {
if(sparkSession == null) {
throw new DMLRuntimeException("SparkSession is not created.");
}
if(outputVector) {
JavaPairRDD rdd = getBinaryBlockedRDD(varName);
if(rdd != null) {
MatrixCharacteristics mc = _outMetadata.get(varName);
return RDDConverterUtils.binaryBlockToDataFrame(sparkSession, rdd, mc, true);
}
throw new DMLRuntimeException("Variable " + varName + " not found in the output symbol table.");
}
else {
return getDF(sparkSession, varName);
}
}
/**
* Obtain the DataFrame
*
* @param sqlContext the SQL Context
* @param varName the variable name
* @param outputVector if true, returns DataFrame with two column: ID and org.apache.spark.ml.linalg.Vector
* @return the DataFrame
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
public Dataset getDF(SQLContext sqlContext, String varName, boolean outputVector) throws DMLRuntimeException {
if (sqlContext == null) {
throw new DMLRuntimeException("SQLContext is not created");
}
SparkSession sparkSession = sqlContext.sparkSession();
return getDF(sparkSession, varName, outputVector);
}
/**
* This methods improves the performance of MLPipeline wrappers.
*
* @param sparkSession the Spark Session
* @param varName the variable name
* @param mc the matrix characteristics
* @return the DataFrame
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
public Dataset getDF(SparkSession sparkSession, String varName, MatrixCharacteristics mc)
throws DMLRuntimeException
{
if(sparkSession == null) {
throw new DMLRuntimeException("SparkSession is not created.");
}
JavaPairRDD binaryBlockRDD = getBinaryBlockedRDD(varName);
return RDDConverterUtils.binaryBlockToDataFrame(sparkSession, binaryBlockRDD, mc, true);
}
/**
* This methods improves the performance of MLPipeline wrappers.
*
* @param sqlContext the SQL Context
* @param varName the variable name
* @param mc the matrix characteristics
* @return the DataFrame
* @throws DMLRuntimeException if DMLRuntimeException occurs
*/
public Dataset getDF(SQLContext sqlContext, String varName, MatrixCharacteristics mc)
throws DMLRuntimeException
{
if (sqlContext == null) {
throw new DMLRuntimeException("SQLContext is not created");
}
SparkSession sparkSession = sqlContext.sparkSession();
return getDF(sparkSession, varName, mc);
}
public JavaRDD getStringRDD(String varName, String format) throws DMLRuntimeException {
if(format.equals("text")) {
JavaPairRDD binaryRDD = getBinaryBlockedRDD(varName);
MatrixCharacteristics mcIn = getMatrixCharacteristics(varName);
return RDDConverterUtils.binaryBlockToTextCell(binaryRDD, mcIn);
}
else {
throw new DMLRuntimeException("The output format:" + format + " is not implemented yet.");
}
}
public JavaRDD getStringFrameRDD(String varName, String format, CSVFileFormatProperties fprop ) throws DMLRuntimeException {
JavaPairRDD binaryRDD = getFrameBinaryBlockedRDD(varName);
MatrixCharacteristics mcIn = getMatrixCharacteristics(varName);
if(format.equals("csv")) {
return FrameRDDConverterUtils.binaryBlockToCsv(binaryRDD, mcIn, fprop, false);
}
else if(format.equals("text")) {
return FrameRDDConverterUtils.binaryBlockToTextCell(binaryRDD, mcIn);
}
else {
throw new DMLRuntimeException("The output format:" + format + " is not implemented yet.");
}
}
public Dataset getDataFrameRDD(String varName, JavaSparkContext jsc) throws DMLRuntimeException {
JavaPairRDD binaryRDD = getFrameBinaryBlockedRDD(varName);
MatrixCharacteristics mcIn = getMatrixCharacteristics(varName);
SparkSession sparkSession = SparkSession.builder().sparkContext(jsc.sc()).getOrCreate();
return FrameRDDConverterUtils.binaryBlockToDataFrame(sparkSession, binaryRDD, mcIn, null);
}
public MLMatrix getMLMatrix(MLContext ml, SparkSession sparkSession, String varName) throws DMLRuntimeException {
if(sparkSession == null) {
throw new DMLRuntimeException("SparkSession is not created.");
}
else if(ml == null) {
throw new DMLRuntimeException("MLContext is not created.");
}
JavaPairRDD rdd = getBinaryBlockedRDD(varName);
if(rdd != null) {
MatrixCharacteristics mc = getMatrixCharacteristics(varName);
StructType schema = MLBlock.getDefaultSchemaForBinaryBlock();
return new MLMatrix(sparkSession.createDataFrame(rdd.map(new GetMLBlock()).rdd(), schema), mc, ml);
}
throw new DMLRuntimeException("Variable " + varName + " not found in the output symbol table.");
}
public MLMatrix getMLMatrix(MLContext ml, SQLContext sqlContext, String varName) throws DMLRuntimeException {
if (sqlContext == null) {
throw new DMLRuntimeException("SQLContext is not created");
}
SparkSession sparkSession = sqlContext.sparkSession();
return getMLMatrix(ml, sparkSession, varName);
}
}