jenniferdai commented on a change in pull request #4253: Add segment pre-processing Hadoop job URL: https://github.com/apache/incubator-pinot/pull/4253#discussion_r290838749
########## File path: pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/SegmentPreprocessingJob.java ########## @@ -0,0 +1,504 @@ +/** + * 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.pinot.hadoop.job; + +import com.google.common.base.Preconditions; +import java.io.IOException; +import java.util.ArrayList; +import java.util.Arrays; +import java.util.HashSet; +import java.util.List; +import java.util.Map; +import java.util.Properties; +import java.util.Set; +import java.util.zip.GZIPInputStream; +import javax.annotation.Nullable; +import org.apache.avro.Schema; +import org.apache.avro.file.DataFileStream; +import org.apache.avro.generic.GenericDatumReader; +import org.apache.avro.generic.GenericRecord; +import org.apache.avro.mapred.AvroKey; +import org.apache.avro.mapred.AvroValue; +import org.apache.avro.mapreduce.AvroJob; +import org.apache.avro.mapreduce.AvroKeyOutputFormat; +import org.apache.avro.mapreduce.AvroMultipleOutputs; +import org.apache.commons.lang3.StringUtils; +import org.apache.hadoop.conf.Configuration; +import org.apache.hadoop.conf.Configured; +import org.apache.hadoop.fs.FileStatus; +import org.apache.hadoop.fs.FileSystem; +import org.apache.hadoop.fs.Path; +import org.apache.hadoop.fs.permission.FsPermission; +import org.apache.hadoop.io.NullWritable; +import org.apache.hadoop.mapred.JobContext; +import org.apache.hadoop.mapreduce.Job; +import org.apache.hadoop.mapreduce.MRJobConfig; +import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; +import org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter; +import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; +import org.apache.hadoop.mapreduce.lib.output.LazyOutputFormat; +import org.apache.pinot.common.Utils; +import org.apache.pinot.common.config.ColumnPartitionConfig; +import org.apache.pinot.common.config.IndexingConfig; +import org.apache.pinot.common.config.SegmentPartitionConfig; +import org.apache.pinot.common.config.TableConfig; +import org.apache.pinot.hadoop.io.CombineAvroKeyInputFormat; +import org.apache.pinot.hadoop.job.mapper.SegmentPreprocessingMapper; +import org.apache.pinot.hadoop.job.partitioners.GenericPartitioner; +import org.apache.pinot.hadoop.job.reducer.SegmentPreprocessingReducer; +import org.apache.pinot.hadoop.utils.PushLocation; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import static org.apache.pinot.hadoop.job.JobConfigConstants.*; + + +public class SegmentPreprocessingJob extends Configured { + private static final Logger _logger = LoggerFactory.getLogger(SegmentPreprocessingJob.class); + private final Properties _properties; + private Configuration _configuration; + + private boolean _enablePartitioning = false; + private boolean _enableSorting = false; + private boolean _enableResizing = false; + + private String _partitionColumn; + private int _numberOfPartitions; + private String _partitionFunction; + private String _sortedColumn; + private int _numberOfOutputFiles; + + private final String _inputSegmentDir; + private final String _preprocessedOutputDir; + protected final String _rawTableName; + + private final String _hdfsDefaultClasspathDir; + private final String _defaultPermissionsMask; + protected final List<PushLocation> _pushLocations; + + private TableConfig _tableConfig; + protected FileSystem _fileSystem; + + public SegmentPreprocessingJob(final Properties properties) { + _properties = properties; + _configuration = new Configuration(); + setConf(_configuration); + _configuration.set("mapreduce.job.user.classpath.first", "true"); + Utils.logVersions(); + logProperties(); + + if (_properties.getProperty(ENABLE_PARTITIONING) != null) { + _enablePartitioning = Boolean.parseBoolean(_properties.getProperty(ENABLE_PARTITIONING)); + } + + if (_properties.getProperty(ENABLE_SORTING) != null) { + _enableSorting = Boolean.parseBoolean(_properties.getProperty(ENABLE_SORTING)); + } + + if (!_enablePartitioning && _properties.getProperty(ENABLE_RESIZING) != null) { + _enableResizing = Boolean.parseBoolean(_properties.getProperty(ENABLE_RESIZING)); + } + + // get input/output paths. + _inputSegmentDir = properties.getProperty(PATH_TO_INPUT); + _preprocessedOutputDir = properties.getProperty(PATH_TO_OUTPUT); + _rawTableName = Preconditions.checkNotNull(_properties.getProperty(JobConfigConstants.SEGMENT_TABLE_NAME)); + + _hdfsDefaultClasspathDir = _properties.getProperty("hdfs.default.classpath.dir", null); + _defaultPermissionsMask = _properties.getProperty(JobConfigConstants.DEFAULT_PERMISSIONS_MASK, null); + + // Optional push location and table parameters. If set, will use the table config and schema from the push hosts. + String pushHostsString = _properties.getProperty(JobConfigConstants.PUSH_TO_HOSTS); + String pushPortString = _properties.getProperty(JobConfigConstants.PUSH_TO_PORT); + if (pushHostsString != null && pushPortString != null) { + _pushLocations = + PushLocation.getPushLocations(StringUtils.split(pushHostsString, ','), Integer.parseInt(pushPortString)); + } else { + _pushLocations = null; + } + + _logger.info("*********************************************************************"); + _logger.info("enable.partitioning: {}", _enablePartitioning); + _logger.info("enable.sorting: {}", _enableSorting); + _logger.info("enable.resizing: {}", _enableResizing); + _logger.info("path.to.input: {}", _inputSegmentDir); + _logger.info("path.to.output: {}", _preprocessedOutputDir); + _logger.info("hdfs.default.classpath.dir: {}", _hdfsDefaultClasspathDir); + _logger.info("push.locations: {}", _pushLocations); + _logger.info("*********************************************************************"); + } + + public void run() throws Exception { + if (!_enablePartitioning && !_enableSorting && !_enableResizing) { + _logger.info("Pre-computing job is disabled."); + return; + } else { + _logger.info("Starting {}", getClass().getSimpleName()); + } + + _fileSystem = FileSystem.get(_configuration); + final List<String> inputDataPath = Arrays.asList(_inputSegmentDir.split("\\s*,\\s*")); + Path outputDir = new Path(_preprocessedOutputDir); + + if (_fileSystem.exists(outputDir)) { + _logger.warn("Found the output folder {}, deleting it", _preprocessedOutputDir); + _fileSystem.delete(outputDir, true); + } + setDirPermission(outputDir); + + _tableConfig = getTableConfig(); + + if (_enablePartitioning) { + fetchPartitioningConfig(); + _logger.info("partition column: {}", _partitionColumn); + _logger.info("number of partitions: {}", _numberOfPartitions); + _logger.info("partition column: {}", _partitionColumn); + } + + if (_enableSorting) { + fetchSortingConfig(); + _logger.info("sorted.column: {}", _sortedColumn); + } + + if (_enableResizing) { + fetchResizingConfig(); + _logger.info("minimum number of output files: {}", _numberOfOutputFiles); + } + + _logger.info("Initializing a pre-computing job"); + Job job = Job.getInstance(_configuration); + + job.getConfiguration().set(JobContext.JOB_NAME, this.getClass().getName()); + job.getConfiguration().set(MRJobConfig.MAPREDUCE_JOB_USER_CLASSPATH_FIRST, "true"); + job.getConfiguration().set(FileOutputCommitter.SUCCESSFUL_JOB_OUTPUT_DIR_MARKER, "false"); + + job.setJarByClass(SegmentPreprocessingJob.class); + + String hadoopTokenFileLocation = System.getenv("HADOOP_TOKEN_FILE_LOCATION"); + if (hadoopTokenFileLocation != null) { + job.getConfiguration().set("mapreduce.job.credentials.binary", hadoopTokenFileLocation); + } + + // Schema configs. + Schema schema = getSchema(inputDataPath.get(0)); + _logger.info("Schema is: {}", schema.toString(true)); + + // Mapper configs. + job.setMapperClass(SegmentPreprocessingMapper.class); + job.setMapOutputKeyClass(AvroKey.class); + job.setMapOutputValueClass(AvroValue.class); + job.getConfiguration().setInt(JobContext.NUM_MAPS, inputDataPath.size()); + + // Reducer configs. + job.setReducerClass(SegmentPreprocessingReducer.class); + job.setOutputKeyClass(AvroKey.class); + job.setOutputValueClass(NullWritable.class); + if (_properties.getProperty(MAXIMUM_NUMBER_OF_RECORDS) != null) { + _logger.info("Setting {} to {}", MAXIMUM_NUMBER_OF_RECORDS, _properties.getProperty(MAXIMUM_NUMBER_OF_RECORDS)); + job.getConfiguration().set(MAXIMUM_NUMBER_OF_RECORDS, _properties.getProperty(MAXIMUM_NUMBER_OF_RECORDS)); + } + AvroMultipleOutputs.addNamedOutput(job, "avro", AvroKeyOutputFormat.class, schema); + AvroMultipleOutputs.setCountersEnabled(job, true); + LazyOutputFormat.setOutputFormatClass(job, AvroKeyOutputFormat.class); + + // Input and output paths. + FileInputFormat.setInputPaths(job, _inputSegmentDir); + FileOutputFormat.setOutputPath(job, outputDir); + + List<FileStatus> inputDataFiles = new ArrayList<>(); + for (String inputPath : inputDataPath) { + Path inputPathPattern = new Path(inputPath); + FileStatus[] fileStatusArr = _fileSystem.globStatus(inputPathPattern); + for (FileStatus fileStatus : fileStatusArr) { + inputDataFiles.addAll(getDataFilesFromPath(_fileSystem, fileStatus.getPath())); + } + } + _logger.info("Total number of files to be pre-computed: {}", inputDataFiles.size()); + + // Set up mapper output key + Set<Schema.Field> fieldSet = new HashSet<>(); + + // Partition configs. + int numReduceTasks = (_numberOfPartitions != 0) ? _numberOfPartitions : inputDataFiles.size(); + if (_partitionColumn != null) { + job.getConfiguration().set(ENABLE_PARTITIONING, "true"); + job.setPartitionerClass(GenericPartitioner.class); + job.getConfiguration().set(PARTITION_COLUMN, _partitionColumn); + if (_partitionFunction != null) { + job.getConfiguration().set(PARTITION_FUNCTION, _partitionFunction); + } + job.getConfiguration().set(NUMBER_OF_PARTITIONS, Integer.toString(numReduceTasks)); + } else { + if (_numberOfOutputFiles > 0) { + numReduceTasks = _numberOfOutputFiles; + } + // Partitioning is disabled. Adding hashcode as one of the fields to mapper output key. + // so that all the rows can be spread evenly. + addHashCodeField(fieldSet); + } + job.setInputFormatClass(CombineAvroKeyInputFormat.class); + + _logger.info("Number of reduce tasks for pre-computing: {}", numReduceTasks); + job.setNumReduceTasks(numReduceTasks); + + // Sort config. + if (_sortedColumn != null) { + _logger.info("Adding sorted column: {} to job config", _sortedColumn); + job.getConfiguration().set(SORTED_COLUMN, _sortedColumn); + + // Sorting is enabled. Adding sorted column value to mapper output key. + Schema sortedColumnSchema = schema.getField(_sortedColumn).schema(); + Schema sortedColumnAsKeySchema; + if (sortedColumnSchema.getType().equals(Schema.Type.UNION)) { + sortedColumnAsKeySchema = Schema.createUnion(sortedColumnSchema.getTypes()); + } else { + sortedColumnAsKeySchema = Schema.create(sortedColumnSchema.getType()); + } + Schema.Field columnField = new Schema.Field(_sortedColumn, sortedColumnAsKeySchema, "sortedColumn", null); + fieldSet.add(columnField); + } else { + // If sorting is disabled, hashcode will be the only factor for sort/group comparator. + addHashCodeField(fieldSet); + } + + Schema mapperOutputKeySchema = Schema.createRecord("record", "", "", false); + mapperOutputKeySchema.setFields(new ArrayList<>(fieldSet)); + _logger.info("Mapper output schema: {}", mapperOutputKeySchema); + + AvroJob.setInputKeySchema(job, schema); + AvroJob.setMapOutputKeySchema(job, mapperOutputKeySchema); + AvroJob.setMapOutputValueSchema(job, schema); + AvroJob.setOutputKeySchema(job, schema); + + // Since we aren't extending AbstractHadoopJob, we need to add the jars for the job to + // distributed cache ourselves. Take a look at how the addFilesToDistributedCache is + // implemented so that you know what it does. + _logger.info("HDFS class path: " + _hdfsDefaultClasspathDir); + if (_hdfsDefaultClasspathDir != null) { + _logger.info("Copying jars locally."); + addContainerLocalFiles(job, _hdfsDefaultClasspathDir, job.getConfiguration()); + } else { + _logger.info("Property 'hdfs.default.classpath.dir' not specified."); + } + + long startTime = System.currentTimeMillis(); + // Submit the job for execution. + job.waitForCompletion(true); + if (!job.isSuccessful()) { + throw new RuntimeException("Job failed : " + job); + } + + _logger.info("Finished pre-computing job in {}ms", (System.currentTimeMillis() - startTime)); + } + + @Nullable + private TableConfig getTableConfig() + throws IOException { + try (ControllerRestApi controllerRestApi = getControllerRestApi()) { + return controllerRestApi != null ? controllerRestApi.getTableConfig() : null; + } + } + + /** + * Can be overridden to provide custom controller Rest API. + */ + @Nullable + private ControllerRestApi getControllerRestApi() { + return _pushLocations != null ? new DefaultControllerRestApi(_pushLocations, _rawTableName) : null; + } + + private void setDirPermission(Path dirPath) + throws IOException { + if (_defaultPermissionsMask != null) { + FsPermission permission = FsPermission.getDirDefault().applyUMask(new FsPermission(_defaultPermissionsMask)); + _logger.info("Setting permission: {} to directory: {}", permission, dirPath); + _fileSystem.setPermission(dirPath, permission); + } + } + + private void fetchPartitioningConfig() { + // Fetch partition info from table config. + SegmentPartitionConfig segmentPartitionConfig = _tableConfig.getIndexingConfig().getSegmentPartitionConfig(); + if (segmentPartitionConfig != null) { + Map<String, ColumnPartitionConfig> columnPartitionMap = segmentPartitionConfig.getColumnPartitionMap(); + assert columnPartitionMap.size() <= 1; + if (columnPartitionMap.size() == 1) { + _partitionColumn = columnPartitionMap.keySet().iterator().next(); + _numberOfPartitions = segmentPartitionConfig.getNumPartitions(_partitionColumn); + _partitionFunction = segmentPartitionConfig.getFunctionName(_partitionColumn); + } + } else { + _logger.info("Segment partition config is null for table: {}", _tableConfig.getTableName()); + } + + // Check whether configs overwritten by Hadoop properties. + if (_properties.getProperty(PARTITION_COLUMN) != null) { + _logger.info("Overriding partition column to: {}", _properties.getProperty(PARTITION_COLUMN)); + _partitionColumn = _properties.getProperty(PARTITION_COLUMN); + } + if (_properties.getProperty(NUMBER_OF_PARTITIONS) != null) { + _logger.info("Overriding partition number to: {}", _properties.getProperty(NUMBER_OF_PARTITIONS)); + _numberOfPartitions = Integer.parseInt(_properties.getProperty(NUMBER_OF_PARTITIONS)); + } + } + + private void fetchSortingConfig() { + // Fetch sorting info from table config. + IndexingConfig indexingConfig = _tableConfig.getIndexingConfig(); + List<String> sortedColumns = indexingConfig.getSortedColumn(); + assert sortedColumns.size() <= 1; + if (sortedColumns.size() == 1) { + _sortedColumn = sortedColumns.get(0); + } + // Check whether configs overwritten by Hadoop properties. + if (_properties.getProperty(SORTED_COLUMN) != null) { + _logger.info("Overriding sorted column to: {}", _properties.getProperty(SORTED_COLUMN)); + _sortedColumn = _properties.getProperty(SORTED_COLUMN); + } + } + + private void fetchResizingConfig() { + if (_properties.getProperty(MINIMUM_NUMBER_OF_OUTPUT_FILES) != null) { + _numberOfOutputFiles = Integer.parseInt(_properties.getProperty(MINIMUM_NUMBER_OF_OUTPUT_FILES)); + } else { + _numberOfOutputFiles = 0; + } + } + + /** + * Finds the avro file in the input folder, and returns its avro schema + * @param inputPathDir Path to input directory + * @return Input schema + * @throws IOException exception when accessing to IO + */ + private static Schema getSchema(String inputPathDir) throws IOException { + FileSystem fs = FileSystem.get(new Configuration()); + Schema avroSchema = null; + for (String input : inputPathDir.split("\\s*,\\s*")) { + Path inputPath = new Path(input); + for (FileStatus fileStatus : fs.listStatus(inputPath)) { + if (fileStatus.isFile() && fileStatus.getPath().getName().endsWith(".avro")) { + _logger.info("Extracting schema from " + fileStatus.getPath()); + avroSchema = extractSchemaFromAvro(fileStatus.getPath()); + break; + } + } + } + return avroSchema; + } + + /** + * Extracts avro schema from avro file + * @param avroFile Input avro file + * @return Schema in avro file + * @throws IOException exception when accessing to IO + */ + private static Schema extractSchemaFromAvro(Path avroFile) throws IOException { + DataFileStream<GenericRecord> dataStreamReader = getAvroReader(avroFile); + Schema avroSchema = dataStreamReader.getSchema(); + dataStreamReader.close(); + return avroSchema; + } + + /** + * Helper method that returns avro reader for the given avro file. + * If file name ends in 'gz' then returns the GZIP version, otherwise gives the regular reader. + * + * @param avroFile File to read + * @return Avro reader for the file. + * @throws IOException exception when accessing to IO + */ + private static DataFileStream<GenericRecord> getAvroReader(Path avroFile) throws IOException { + FileSystem fs = FileSystem.get(new Configuration()); + if (avroFile.getName().endsWith("gz")) { + return new DataFileStream<>(new GZIPInputStream(fs.open(avroFile)), new GenericDatumReader<>()); + } else { + return new DataFileStream<>(fs.open(avroFile), new GenericDatumReader<>()); + } + } + + private ArrayList<FileStatus> getDataFilesFromPath(FileSystem fs, Path inBaseDir) throws IOException { Review comment: what about orc? 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