mcvsubbu commented on a change in pull request #7062:
URL: https://github.com/apache/incubator-pinot/pull/7062#discussion_r655698884
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/InternalConfigConstants.java
##########
@@ -31,19 +31,23 @@
public static final String SEGMENT_TIME_FORMAT = "segment.time.format";
public static final String SEGMENT_TIME_SDF_PATTERN =
"segment.time.sdf.pattern";
+ // The operations of preprocessing that is enabled.
+ public static final String PREPROCESS_OPERATIONS =
"preprocessing.operations";
+
// Partitioning configs
public static final String PARTITION_COLUMN_CONFIG = "partition.column";
public static final String NUM_PARTITIONS_CONFIG = "num.partitions";
public static final String PARTITION_FUNCTION_CONFIG = "partition.function";
- public static final String SORTED_COLUMN_CONFIG = "sorted.column";
+ public static final String SORTING_COLUMN_CONFIG = "sorting.column";
+ public static final String SORTING_COLUMN_TYPE = "sorting.type";
public static final String ENABLE_PARTITIONING = "enable.partitioning";
// max records per file in each partition. No effect otherwise.
- public static final String PARTITION_MAX_RECORDS_PER_FILE =
"partition.max.records.per.file";
+ public static final String PREPROCESSING_MAX_NUM_RECORDS_PER_FILE =
"preprocessing.max.num.records.per.file";
Review comment:
Hope nobody is using this, otherwise you need to accept both configs and
use the more recent one if defined.
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/preprocess/AvroDataPreprocessingHelper.java
##########
@@ -0,0 +1,155 @@
+/**
+ * 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.preprocess;
+
+import com.google.common.base.Preconditions;
+import java.io.IOException;
+import java.util.List;
+import java.util.zip.GZIPInputStream;
+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.mapreduce.AvroJob;
+import org.apache.avro.mapreduce.AvroKeyInputFormat;
+import org.apache.avro.mapreduce.AvroKeyOutputFormat;
+import org.apache.avro.mapreduce.AvroMultipleOutputs;
+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.NullWritable;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.Partitioner;
+import org.apache.hadoop.mapreduce.lib.output.LazyOutputFormat;
+import org.apache.pinot.hadoop.job.mappers.AvroDataPreprocessingMapper;
+import
org.apache.pinot.hadoop.job.partitioners.AvroDataPreprocessingPartitioner;
+import org.apache.pinot.hadoop.job.reducers.AvroDataPreprocessingReducer;
+import org.apache.pinot.hadoop.utils.preprocess.HadoopUtils;
+import org.apache.pinot.segment.spi.partition.PartitionFunctionFactory;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+
+public class AvroDataPreprocessingHelper extends DataPreprocessingHelper {
+ private static final Logger LOGGER =
LoggerFactory.getLogger(AvroDataPreprocessingHelper.class);
+
+ public AvroDataPreprocessingHelper(List<Path> inputDataPaths, Path
outputPath) {
+ super(inputDataPaths, outputPath);
+ }
+
+ @Override
+ public Class<? extends Partitioner> getPartitioner() {
+ return AvroDataPreprocessingPartitioner.class;
+ }
+
+ @Override
+ public void setUpMapperReducerConfigs(Job job)
+ throws IOException {
+ Schema avroSchema = getAvroSchema(_sampleRawDataPath);
+ LOGGER.info("Avro schema is: {}", avroSchema.toString(true));
+ validateConfigsAgainstSchema(avroSchema);
+
+ job.setInputFormatClass(AvroKeyInputFormat.class);
+ job.setMapperClass(AvroDataPreprocessingMapper.class);
+
+ job.setReducerClass(AvroDataPreprocessingReducer.class);
+ AvroMultipleOutputs.addNamedOutput(job, "avro", AvroKeyOutputFormat.class,
avroSchema);
+ AvroMultipleOutputs.setCountersEnabled(job, true);
+ // Use LazyOutputFormat to avoid creating empty files.
+ LazyOutputFormat.setOutputFormatClass(job, AvroKeyOutputFormat.class);
+ job.setOutputKeyClass(AvroKey.class);
+ job.setOutputValueClass(NullWritable.class);
+
+ AvroJob.setInputKeySchema(job, avroSchema);
+ AvroJob.setMapOutputValueSchema(job, avroSchema);
+ AvroJob.setOutputKeySchema(job, avroSchema);
+ }
+
+ @Override
+ String getSampleTimeColumnValue(String timeColumnName)
+ throws IOException {
+ String sampleTimeColumnValue;
+ try (DataFileStream<GenericRecord> dataStreamReader =
getAvroReader(_sampleRawDataPath)) {
+ sampleTimeColumnValue =
dataStreamReader.next().get(timeColumnName).toString();
+ }
+ return sampleTimeColumnValue;
+ }
+
+ /**
+ * 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 Schema getAvroSchema(Path inputPathDir)
+ throws IOException {
+ Schema avroSchema = null;
+ for (FileStatus fileStatus :
HadoopUtils.DEFAULT_FILE_SYSTEM.listStatus(inputPathDir)) {
+ if (fileStatus.isFile() &&
fileStatus.getPath().getName().endsWith(".avro")) {
+ LOGGER.info("Extracting schema from " + fileStatus.getPath());
+ try (DataFileStream<GenericRecord> dataStreamReader =
getAvroReader(inputPathDir)) {
+ avroSchema = dataStreamReader.getSchema();
+ }
+ break;
+ }
+ }
+ 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
+ */
+ protected DataFileStream<GenericRecord> getAvroReader(Path avroFile)
Review comment:
why protected?
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/HadoopSegmentPreprocessingJob.java
##########
@@ -215,123 +158,84 @@ private void fetchPartitioningConfig() {
_partitionFunction =
segmentPartitionConfig.getFunctionName(_partitionColumn);
}
} else {
- _logger.info("Segment partition config is null for table: {}",
_tableConfig.getTableName());
+ LOGGER.info("Segment partition config is null for table: {}",
_tableConfig.getTableName());
}
}
private void fetchSortingConfig() {
- // Fetch sorting info from table config.
+ if (!_preprocessingOperations.contains("sort")) {
+ LOGGER.info("Sorting is disabled.");
+ return;
+ }
+ // Fetch sorting info from table config first.
+ List<String> sortingColumns = new ArrayList<>();
+ List<FieldConfig> fieldConfigs = _tableConfig.getFieldConfigList();
+ if (fieldConfigs != null && !fieldConfigs.isEmpty()) {
+ for (FieldConfig fieldConfig : fieldConfigs) {
+ if (fieldConfig.getIndexType() == FieldConfig.IndexType.SORTED) {
+ sortingColumns.add(fieldConfig.getName());
+ }
+ }
+ }
+ if (!sortingColumns.isEmpty()) {
+ Preconditions.checkArgument(sortingColumns.size() == 1, "There should be
at most 1 sorted column in the table.");
+ _sortingColumn = sortingColumns.get(0);
+ return;
+ }
+
+ // There is no sorted column specified in field configs, try to find
sorted column from indexing config.
IndexingConfig indexingConfig = _tableConfig.getIndexingConfig();
List<String> sortedColumns = indexingConfig.getSortedColumn();
if (sortedColumns != null) {
Preconditions.checkArgument(sortedColumns.size() <= 1, "There should be
at most 1 sorted column in the table.");
if (sortedColumns.size() == 1) {
- _sortedColumn = sortedColumns.get(0);
+ _sortingColumn = sortedColumns.get(0);
+ FieldSpec fieldSpec =
_pinotTableSchema.getFieldSpecFor(_sortingColumn);
+ Preconditions.checkState(fieldSpec != null, "Failed to find sorting
column: {} in the schema", _sortingColumn);
+ Preconditions
+ .checkState(fieldSpec.isSingleValueField(), "Cannot sort on
multi-value column: %s", _sortingColumn);
+ _sortingColumnType = fieldSpec.getDataType();
+ Preconditions.checkState(_sortingColumnType !=
FieldSpec.DataType.BYTES, "Cannot sort on BYTES column: %s",
Review comment:
Now we have a whole bunch of column types: JSON, STRUCT, MAP, LIST.
Maybe you should add a method in FieldSpec.DataType like `canBeASortedColumn()`
and just invoke that?
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/preprocess/AvroDataPreprocessingHelper.java
##########
@@ -0,0 +1,155 @@
+/**
+ * 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.preprocess;
+
+import com.google.common.base.Preconditions;
+import java.io.IOException;
+import java.util.List;
+import java.util.zip.GZIPInputStream;
+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.mapreduce.AvroJob;
+import org.apache.avro.mapreduce.AvroKeyInputFormat;
+import org.apache.avro.mapreduce.AvroKeyOutputFormat;
+import org.apache.avro.mapreduce.AvroMultipleOutputs;
+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.NullWritable;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.Partitioner;
+import org.apache.hadoop.mapreduce.lib.output.LazyOutputFormat;
+import org.apache.pinot.hadoop.job.mappers.AvroDataPreprocessingMapper;
+import
org.apache.pinot.hadoop.job.partitioners.AvroDataPreprocessingPartitioner;
+import org.apache.pinot.hadoop.job.reducers.AvroDataPreprocessingReducer;
+import org.apache.pinot.hadoop.utils.preprocess.HadoopUtils;
+import org.apache.pinot.segment.spi.partition.PartitionFunctionFactory;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+
+public class AvroDataPreprocessingHelper extends DataPreprocessingHelper {
+ private static final Logger LOGGER =
LoggerFactory.getLogger(AvroDataPreprocessingHelper.class);
+
+ public AvroDataPreprocessingHelper(List<Path> inputDataPaths, Path
outputPath) {
+ super(inputDataPaths, outputPath);
+ }
+
+ @Override
+ public Class<? extends Partitioner> getPartitioner() {
+ return AvroDataPreprocessingPartitioner.class;
+ }
+
+ @Override
+ public void setUpMapperReducerConfigs(Job job)
+ throws IOException {
+ Schema avroSchema = getAvroSchema(_sampleRawDataPath);
+ LOGGER.info("Avro schema is: {}", avroSchema.toString(true));
+ validateConfigsAgainstSchema(avroSchema);
+
+ job.setInputFormatClass(AvroKeyInputFormat.class);
+ job.setMapperClass(AvroDataPreprocessingMapper.class);
+
+ job.setReducerClass(AvroDataPreprocessingReducer.class);
+ AvroMultipleOutputs.addNamedOutput(job, "avro", AvroKeyOutputFormat.class,
avroSchema);
Review comment:
Can you use `RawDataFormat.AVRO.name()` here?
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/HadoopSegmentPreprocessingJob.java
##########
@@ -199,11 +122,31 @@ public void run()
throw new RuntimeException("Job failed : " + job);
}
- _logger.info("Finished pre-processing job in {}ms",
(System.currentTimeMillis() - startTime));
+ LOGGER.info("Finished pre-processing job in {}ms",
(System.currentTimeMillis() - startTime));
+ }
+
+ private void fetchPreProcessingOperations() {
+ _preprocessingOperations = new HashSet<>();
+ TableCustomConfig customConfig = _tableConfig.getCustomConfig();
+ if (customConfig != null) {
+ Map<String, String> customConfigMap = customConfig.getCustomConfigs();
+ if (customConfigMap != null && !customConfigMap.isEmpty()) {
+ String preprocessingOperationsString =
+
customConfigMap.getOrDefault(InternalConfigConstants.PREPROCESS_OPERATIONS, "");
+ String[] preprocessingOpsArray =
preprocessingOperationsString.split(",");
Review comment:
May be a good idea to parse and split each one of them into an enum, and
use enums later? Think about it.
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/HadoopSegmentPreprocessingJob.java
##########
@@ -215,123 +158,84 @@ private void fetchPartitioningConfig() {
_partitionFunction =
segmentPartitionConfig.getFunctionName(_partitionColumn);
}
} else {
- _logger.info("Segment partition config is null for table: {}",
_tableConfig.getTableName());
+ LOGGER.info("Segment partition config is null for table: {}",
_tableConfig.getTableName());
}
}
private void fetchSortingConfig() {
- // Fetch sorting info from table config.
+ if (!_preprocessingOperations.contains("sort")) {
+ LOGGER.info("Sorting is disabled.");
+ return;
+ }
+ // Fetch sorting info from table config first.
+ List<String> sortingColumns = new ArrayList<>();
+ List<FieldConfig> fieldConfigs = _tableConfig.getFieldConfigList();
+ if (fieldConfigs != null && !fieldConfigs.isEmpty()) {
+ for (FieldConfig fieldConfig : fieldConfigs) {
+ if (fieldConfig.getIndexType() == FieldConfig.IndexType.SORTED) {
+ sortingColumns.add(fieldConfig.getName());
+ }
+ }
+ }
+ if (!sortingColumns.isEmpty()) {
+ Preconditions.checkArgument(sortingColumns.size() == 1, "There should be
at most 1 sorted column in the table.");
+ _sortingColumn = sortingColumns.get(0);
+ return;
+ }
+
+ // There is no sorted column specified in field configs, try to find
sorted column from indexing config.
IndexingConfig indexingConfig = _tableConfig.getIndexingConfig();
List<String> sortedColumns = indexingConfig.getSortedColumn();
if (sortedColumns != null) {
Preconditions.checkArgument(sortedColumns.size() <= 1, "There should be
at most 1 sorted column in the table.");
if (sortedColumns.size() == 1) {
- _sortedColumn = sortedColumns.get(0);
+ _sortingColumn = sortedColumns.get(0);
+ FieldSpec fieldSpec =
_pinotTableSchema.getFieldSpecFor(_sortingColumn);
+ Preconditions.checkState(fieldSpec != null, "Failed to find sorting
column: {} in the schema", _sortingColumn);
+ Preconditions
+ .checkState(fieldSpec.isSingleValueField(), "Cannot sort on
multi-value column: %s", _sortingColumn);
+ _sortingColumnType = fieldSpec.getDataType();
+ Preconditions.checkState(_sortingColumnType !=
FieldSpec.DataType.BYTES, "Cannot sort on BYTES column: %s",
+ _sortingColumn);
+ LOGGER.info("Sorting the data with column: {} of type: {}",
_sortingColumn, _sortingColumnType);
}
}
}
private void fetchResizingConfig() {
+ if (!_preprocessingOperations.contains("resize")) {
+ LOGGER.info("Resizing is disabled.");
+ return;
+ }
TableCustomConfig tableCustomConfig = _tableConfig.getCustomConfig();
if (tableCustomConfig == null) {
_numOutputFiles = 0;
return;
}
Map<String, String> customConfigsMap =
tableCustomConfig.getCustomConfigs();
- if (customConfigsMap != null &&
customConfigsMap.containsKey(InternalConfigConstants.PREPROCESS_NUM_FILES)) {
- _numOutputFiles =
Integer.parseInt(customConfigsMap.get(InternalConfigConstants.PREPROCESS_NUM_FILES));
+ if (customConfigsMap != null &&
customConfigsMap.containsKey(InternalConfigConstants.PREPROCESSING_NUM_REDUCERS))
{
+ _numOutputFiles =
Integer.parseInt(customConfigsMap.get(InternalConfigConstants.PREPROCESSING_NUM_REDUCERS));
Preconditions.checkState(_numOutputFiles > 0, String
- .format("The value of %s should be positive! Current value: %s",
InternalConfigConstants.PREPROCESS_NUM_FILES,
- _numOutputFiles));
+ .format("The value of %s should be positive! Current value: %s",
+ InternalConfigConstants.PREPROCESSING_NUM_REDUCERS,
_numOutputFiles));
} else {
_numOutputFiles = 0;
}
- }
- private void setMaxNumRecordsConfigIfSpecified(Job job) {
- TableCustomConfig tableCustomConfig = _tableConfig.getCustomConfig();
- if (tableCustomConfig == null) {
- return;
- }
- Map<String, String> customConfigsMap =
tableCustomConfig.getCustomConfigs();
if (customConfigsMap != null && customConfigsMap
- .containsKey(InternalConfigConstants.PARTITION_MAX_RECORDS_PER_FILE)) {
+
.containsKey(InternalConfigConstants.PREPROCESSING_MAX_NUM_RECORDS_PER_FILE)) {
int maxNumRecords =
-
Integer.parseInt(customConfigsMap.get(InternalConfigConstants.PARTITION_MAX_RECORDS_PER_FILE));
+
Integer.parseInt(customConfigsMap.get(InternalConfigConstants.PREPROCESSING_MAX_NUM_RECORDS_PER_FILE));
Preconditions.checkArgument(maxNumRecords > 0,
- "The value of " +
InternalConfigConstants.PARTITION_MAX_RECORDS_PER_FILE
+ "The value of " +
InternalConfigConstants.PREPROCESSING_MAX_NUM_RECORDS_PER_FILE
Review comment:
Should we have an in-built max number of files as well? Some check to
make sure that we are not getting a million 1-record file? Can be a TODO
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/mappers/OrcDataPreprocessingMapper.java
##########
@@ -0,0 +1,87 @@
+/**
+ * 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.mappers;
+
+import com.google.common.base.Preconditions;
+import java.io.IOException;
+import java.util.List;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.io.NullWritable;
+import org.apache.hadoop.io.WritableComparable;
+import org.apache.hadoop.mapreduce.Mapper;
+import org.apache.orc.mapred.OrcStruct;
+import org.apache.orc.mapred.OrcValue;
+import org.apache.pinot.hadoop.job.InternalConfigConstants;
+import org.apache.pinot.hadoop.utils.preprocess.DataPreprocessingUtils;
+import org.apache.pinot.hadoop.utils.preprocess.OrcUtils;
+import org.apache.pinot.spi.data.FieldSpec;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+
+public class OrcDataPreprocessingMapper extends Mapper<NullWritable,
OrcStruct, WritableComparable, OrcValue> {
+ private static final Logger LOGGER =
LoggerFactory.getLogger(OrcDataPreprocessingMapper.class);
+
+ private final OrcValue _valueWrapper = new OrcValue();
+ private String _sortingColumn = null;
+ private FieldSpec.DataType _sortingColumnType = null;
+ private int _sortingColumnId = -1;
+
+ @Override
+ public void setup(Context context) {
+ Configuration configuration = context.getConfiguration();
+ String sortingColumnConfig =
configuration.get(InternalConfigConstants.SORTING_COLUMN_CONFIG);
+ if (sortingColumnConfig != null) {
+ _sortingColumn = sortingColumnConfig;
+ _sortingColumnType =
FieldSpec.DataType.valueOf(configuration.get(InternalConfigConstants.SORTING_COLUMN_TYPE));
+ LOGGER.info("Initialized OrcDataPreprocessingMapper with sortingColumn:
{} of type: {}", _sortingColumn,
+ _sortingColumnType);
+ } else {
+ LOGGER.info("Initialized OrcDataPreprocessingMapper without sorting
column");
+ }
+ }
+
+ @Override
+ public void map(NullWritable key, OrcStruct value, Context context)
+ throws IOException, InterruptedException {
+ _valueWrapper.value = value;
+ if (_sortingColumn != null) {
+ if (_sortingColumnId == -1) {
+ List<String> fieldNames = value.getSchema().getFieldNames();
+ _sortingColumnId = fieldNames.indexOf(_sortingColumn);
+ Preconditions.checkState(_sortingColumnId != -1, "Failed to find
sorting column: %s in the ORC fields: %s",
+ _sortingColumn, fieldNames);
+ LOGGER.info("Field id for sorting column: {} is: {}", _sortingColumn,
_sortingColumnId);
Review comment:
Will this log appear for each record processed?
##########
File path:
pinot-plugins/pinot-batch-ingestion/v0_deprecated/pinot-hadoop/src/main/java/org/apache/pinot/hadoop/job/mappers/SegmentPreprocessingMapper.java
##########
@@ -130,4 +131,26 @@ public void map(AvroKey<GenericRecord> record,
NullWritable value, final Context
throw e;
}
}
+
+ protected void logConfigurations() {
+ StringBuilder stringBuilder = new StringBuilder();
+ stringBuilder.append('{');
+ boolean firstEntry = true;
+ for (Map.Entry<String, String> entry : _jobConf) {
+ if (!firstEntry) {
+ stringBuilder.append(", ");
+ } else {
+ firstEntry = false;
+ }
+
+ stringBuilder.append(entry.getKey());
+ stringBuilder.append('=');
+ stringBuilder.append(entry.getValue());
+ }
+ stringBuilder.append('}');
+
+
LOGGER.info("*********************************************************************");
+ LOGGER.info("Job Configurations: {}", stringBuilder.toString());
Review comment:
Will this be one very long log line? Will be a good idea to add some
newlines in the stringbuilder.append above.
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