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Declarative Machine Learning
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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.sysml.runtime.io;

import java.io.BufferedWriter;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;
import java.io.OutputStreamWriter;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.mapred.JobConf;

import org.apache.sysml.conf.ConfigurationManager;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.DMLUnsupportedOperationException;
import org.apache.sysml.runtime.matrix.CSVReblockMR;
import org.apache.sysml.runtime.matrix.data.CSVFileFormatProperties;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.data.SparseRow;
import org.apache.sysml.runtime.util.MapReduceTool;

/**
 * 
 */
public class WriterTextCSV extends MatrixWriter
{
	//blocksize for string concatenation in order to prevent write OOM 
	//(can be set to very large value to disable blocking)
	public static final int BLOCKSIZE_J = 32; //32 cells (typically ~512B, should be less than write buffer of 1KB)
	
	protected CSVFileFormatProperties _props = null;
	
	public WriterTextCSV( CSVFileFormatProperties props ) {
		_props = props;
	}
	
	@Override
	public void writeMatrixToHDFS(MatrixBlock src, String fname, long rlen, long clen, int brlen, int bclen, long nnz) 
		throws IOException, DMLRuntimeException, DMLUnsupportedOperationException 
	{
		//validity check matrix dimensions
		if( src.getNumRows() != rlen || src.getNumColumns() != clen ) {
			throw new IOException("Matrix dimensions mismatch with metadata: "+src.getNumRows()+"x"+src.getNumColumns()+" vs "+rlen+"x"+clen+".");
		}
		
		//prepare file access
		JobConf job = new JobConf(ConfigurationManager.getCachedJobConf());
		Path path = new Path( fname );

		//if the file already exists on HDFS, remove it.
		MapReduceTool.deleteFileIfExistOnHDFS( fname );
			
		//core write
		writeCSVMatrixToHDFS(path, job, src, rlen, clen, nnz, _props);
	}

	@Override
	public void writeEmptyMatrixToHDFS(String fname, long rlen, long clen, int brlen, int bclen) 
		throws IOException, DMLRuntimeException 
	{
		JobConf job = new JobConf(ConfigurationManager.getCachedJobConf());
		Path path = new Path( fname );

		MatrixBlock src = new MatrixBlock((int)rlen, 1, true);
		writeCSVMatrixToHDFS(path, job, src, brlen, clen, 0, _props);
	}
	
	/**
	 * 
	 * @param fileName
	 * @param src
	 * @param rlen
	 * @param clen
	 * @param nnz
	 * @throws IOException
	 */
	protected void writeCSVMatrixToHDFS( Path path, JobConf job, MatrixBlock src, long rlen, long clen, long nnz, CSVFileFormatProperties props )
		throws IOException
	{
		boolean sparse = src.isInSparseFormat();
		FileSystem fs = FileSystem.get(job);
        BufferedWriter br=new BufferedWriter(new OutputStreamWriter(fs.create(path,true)));		
		
		try
		{
			//for obj reuse and preventing repeated buffer re-allocations
			StringBuilder sb = new StringBuilder();
			
			props = (props==null)? new CSVFileFormatProperties() : props;
			String delim = props.getDelim();
			boolean csvsparse = props.isSparse();
			
			// Write header line, if needed
			if( props.hasHeader() ) 
			{
				//write row chunk-wise to prevent OOM on large number of columns
				for( int bj=0; bj files=new ArrayList();
			for(FileStatus stat: hdfs.listStatus(srcFilePath, CSVReblockMR.hiddenFileFilter))
				files.add(stat.getPath());
			Collections.sort(files);
		
			// first part file path
			Path firstpart = files.get(0);
			
			// create a temp file, and add header and contents of first part
			Path tmp = new Path(firstpart.toString() + ".tmp");
			OutputStream out = hdfs.create(tmp, true);
			out.write(sb.toString().getBytes());
			sb.setLength(0);
			
			// copy rest of the data from firstpart
			InputStream in = null;
			try {
				in = hdfs.open(firstpart);
				IOUtils.copyBytes(in, out, conf, true);
			} finally {
				IOUtilFunctions.closeSilently(in);
				IOUtilFunctions.closeSilently(out);
			}
			
			// rename tmp to firstpart
			hdfs.delete(firstpart, true);
			hdfs.rename(tmp, firstpart);
			
			// rename srcfile to destFile
			hdfs.delete(destFilePath, true);
			hdfs.createNewFile(destFilePath); // force the creation of directory structure
			hdfs.delete(destFilePath, true);  // delete the file, but preserve the directory structure
			hdfs.rename(srcFilePath, destFilePath); // move the data 
		
		} else if (hdfs.isFile(srcFilePath)) {
			// create destination file
			OutputStream out = hdfs.create(destFilePath, true);
			
			// write header
			out.write(sb.toString().getBytes());
			sb.setLength(0);
			
			// copy the data from srcFile
			InputStream in = null;
			try {
				in = hdfs.open(srcFilePath);
				IOUtils.copyBytes(in, out, conf, true);
			} 
			finally {
				IOUtilFunctions.closeSilently(in);
				IOUtilFunctions.closeSilently(out);
			}
		} else {
			throw new IOException(srcFilePath.toString() + ": No such file or directory");
		}
	}
}