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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2020/08/03 21:23:56 UTC
[GitHub] [beam] chamikaramj commented on a change in pull request #12223: [Beam-4379] Make ParquetIO read splittable
chamikaramj commented on a change in pull request #12223:
URL: https://github.com/apache/beam/pull/12223#discussion_r464659415
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -177,6 +214,10 @@ public Read from(String filepattern) {
return from(ValueProvider.StaticValueProvider.of(filepattern));
}
+ public Read withSplit() {
Review comment:
Why do we need this option ? We should be able to safely always enable splitting for runners that support SDF without an explicit flag from the user.
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
Review comment:
We should be able to get rid of this fork by using a single DoFn.
##########
File path: sdks/java/io/parquet/src/test/java/org/apache/beam/sdk/io/parquet/ParquetIOTest.java
##########
@@ -84,11 +85,31 @@ public void testWriteAndRead() {
PCollection<GenericRecord> readBack =
readPipeline.apply(
ParquetIO.read(SCHEMA).from(temporaryFolder.getRoot().getAbsolutePath() + "/*"));
-
PAssert.that(readBack).containsInAnyOrder(records);
readPipeline.run().waitUntilFinish();
}
+ @Test
+ public void testWriteAndReadWithSplit() {
+ List<GenericRecord> records = generateGenericRecords(1000);
Review comment:
Please add a comprehensive set of unit tests for ParquetIO and BlockTracker splitting and progress tracking. You can use following for inspiration.
https://github.com/apache/beam/blob/master/sdks/java/core/src/test/java/org/apache/beam/sdk/io/AvroSourceTest.java
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
+ return input
+ .apply(ParDo.of(new SplitReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ } else {
+ return input
+ .apply(ParDo.of(new ReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ }
+ }
+
+ @DoFn.BoundedPerElement
+ static class SplitReadFn extends DoFn<FileIO.ReadableFile, GenericRecord> {
+ private Class<? extends GenericData> modelClass;
+ private static final Logger LOG = LoggerFactory.getLogger(SplitReadFn.class);
+ private static final long SPLIT_LIMIT = 64000000;
+ ReadSupport<GenericRecord> readSupport;
+
+ SplitReadFn(GenericData model) {
+ this.modelClass = model != null ? model.getClass() : null;
+ }
+
+ private static <K, V> Map<K, Set<V>> toSetMultiMap(Map<K, V> map) {
+ Map<K, Set<V>> setMultiMap = new HashMap<K, Set<V>>();
+ for (Map.Entry<K, V> entry : map.entrySet()) {
+ Set<V> set = new HashSet<V>();
+ set.add(entry.getValue());
+ setMultiMap.put(entry.getKey(), Collections.unmodifiableSet(set));
+ }
+ return Collections.unmodifiableMap(setMultiMap);
+ }
+
+ private InputFile getInputFile(FileIO.ReadableFile file) throws IOException {
+ if (!file.getMetadata().isReadSeekEfficient()) {
+ throw new RuntimeException(
+ String.format("File has to be seekable: %s", file.getMetadata().resourceId()));
+ }
+ return new BeamParquetInputFile(file.openSeekable());
+ }
+
+ @ProcessElement
+ public void processElement(
+ @Element FileIO.ReadableFile file,
+ RestrictionTracker<OffsetRange, Long> tracker,
+ OutputReceiver<GenericRecord> outputReceiver)
+ throws Exception {
+ ReadSupport<GenericRecord> readSupport;
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ readSupport = new AvroReadSupport<GenericRecord>(model);
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ Filter filter = checkNotNull(options.getRecordFilter(), "filter");
+ conf = ((HadoopReadOptions) options).getConf();
+ for (String property : options.getPropertyNames()) {
+ conf.set(property, options.getProperty(property));
+ }
+ FileMetaData parquetFileMetadata = reader.getFooter().getFileMetaData();
+ MessageType fileSchema = parquetFileMetadata.getSchema();
+ Map<String, String> fileMetadata = parquetFileMetadata.getKeyValueMetaData();
+
+ ReadSupport.ReadContext readContext =
+ readSupport.init(new InitContext(conf, toSetMultiMap(fileMetadata), fileSchema));
+ ColumnIOFactory columnIOFactory = new ColumnIOFactory(parquetFileMetadata.getCreatedBy());
+ MessageType requestedSchema = readContext.getRequestedSchema();
+ RecordMaterializer<GenericRecord> recordConverter =
+ readSupport.prepareForRead(conf, fileMetadata, fileSchema, readContext);
+ boolean strictTypeChecking = options.isEnabled(STRICT_TYPE_CHECKING, true);
+ boolean filterRecords = options.useRecordFilter();
+ reader.setRequestedSchema(requestedSchema);
+ MessageColumnIO columnIO =
+ columnIOFactory.getColumnIO(requestedSchema, fileSchema, strictTypeChecking);
+ long currentBlock = tracker.currentRestriction().getFrom();
+ for (int i = 0; i < currentBlock; i++) {
+ reader.skipNextRowGroup();
+ }
+ while (tracker.tryClaim(currentBlock)) {
+
+ LOG.info("reading block" + currentBlock);
+ PageReadStore pages = reader.readNextRowGroup();
+ currentBlock += 1;
+ RecordReader<GenericRecord> recordReader =
+ columnIO.getRecordReader(
+ pages, recordConverter, filterRecords ? filter : FilterCompat.NOOP);
+ long currentRow = 0;
+ long totalRows = pages.getRowCount();
+ while (currentRow < totalRows) {
+ try {
+ GenericRecord record;
+ currentRow += 1;
+ try {
+ record = recordReader.read();
+ } catch (RecordMaterializer.RecordMaterializationException e) {
+ LOG.debug("skipping a corrupt record");
+ continue;
+ }
+ if (recordReader.shouldSkipCurrentRecord()) {
+ // this record is being filtered via the filter2 package
+ LOG.debug("skipping record");
+ continue;
+ }
+ if (record == null) {
+ // only happens with FilteredRecordReader at end of block
+ LOG.debug("filtered record reader reached end of block");
+ break;
+ }
+ if (tracker instanceof BlockTracker) {
+ ((BlockTracker) tracker).makeProgress();
+ }
+ outputReceiver.output(record);
+ } catch (RuntimeException e) {
+ throw new ParquetDecodingException(
+ format(
+ "Can not read value at %d in block %d in file %s",
+ currentRow, currentBlock, file.toString()),
+ e);
+ }
+ }
+ LOG.info("finish read " + currentRow + " rows");
+ }
+ }
+
+ private Configuration setConf() throws Exception {
+ Configuration conf = new Configuration();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ if (model != null
+ && (model.getClass() == GenericData.class || model.getClass() == SpecificData.class)) {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, true);
+ } else {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, false);
+ }
+ return conf;
+ }
+
+ @GetInitialRestriction
+ public OffsetRange getInitialRestriction(@Element FileIO.ReadableFile file) throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ return new OffsetRange(0, reader.getRowGroups().size());
+ }
+
+ @SplitRestriction
+ public void split(
+ @Restriction OffsetRange restriction,
+ OutputReceiver<OffsetRange> out,
+ @Element FileIO.ReadableFile file)
+ throws Exception {
+ long start = restriction.getFrom();
+ long end = restriction.getFrom();
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ List<BlockMetaData> rowGroups = reader.getRowGroups();
+ long totalSize = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ totalSize += rowGroups.get((int) i).getTotalByteSize();
+ end += 1;
+ if (totalSize > SPLIT_LIMIT) {
+ start = end;
+ totalSize = 0;
+ out.output(new OffsetRange(start, end));
+ }
+ }
+ if (totalSize != 0) {
+ out.output(new OffsetRange(start, end));
+ }
+ }
+
+ @NewTracker
+ public RestrictionTracker<OffsetRange, Long> newTracker(
+ @Restriction OffsetRange restriction, @Element FileIO.ReadableFile file)
+ throws Exception {
+ return new BlockTracker(
+ restriction, (long) getSize(file, restriction), getRecordCount(file, restriction));
+ }
+
+ @GetRestrictionCoder
+ public OffsetRange.Coder getRestrictionCoder() {
+ return new OffsetRange.Coder();
+ }
+
+ public long getRecordCount(
+ @Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ long recordCount = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ recordCount += reader.getRowGroups().get((int) i).getRowCount();
+ }
+ return recordCount;
+ }
+ }
+
+ public double getSize(@Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ double size = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ size += reader.getRowGroups().get((int) i).getTotalByteSize();
+ }
+ return size;
+ }
+ }
+ }
+
+ private static class BlockTracker extends OffsetRangeTracker {
+ private long totalWork;
+ private long progress;
+ private long recordSize;
+
+ public BlockTracker(OffsetRange range, long totalWork, long recordCount) {
+ super(range);
+ this.recordSize = totalWork / recordCount;
Review comment:
Let's call this approximateRecordSize
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
+ return input
+ .apply(ParDo.of(new SplitReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ } else {
+ return input
+ .apply(ParDo.of(new ReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ }
+ }
+
+ @DoFn.BoundedPerElement
+ static class SplitReadFn extends DoFn<FileIO.ReadableFile, GenericRecord> {
+ private Class<? extends GenericData> modelClass;
+ private static final Logger LOG = LoggerFactory.getLogger(SplitReadFn.class);
+ private static final long SPLIT_LIMIT = 64000000;
+ ReadSupport<GenericRecord> readSupport;
+
+ SplitReadFn(GenericData model) {
+ this.modelClass = model != null ? model.getClass() : null;
+ }
+
+ private static <K, V> Map<K, Set<V>> toSetMultiMap(Map<K, V> map) {
+ Map<K, Set<V>> setMultiMap = new HashMap<K, Set<V>>();
+ for (Map.Entry<K, V> entry : map.entrySet()) {
+ Set<V> set = new HashSet<V>();
+ set.add(entry.getValue());
+ setMultiMap.put(entry.getKey(), Collections.unmodifiableSet(set));
+ }
+ return Collections.unmodifiableMap(setMultiMap);
+ }
+
+ private InputFile getInputFile(FileIO.ReadableFile file) throws IOException {
+ if (!file.getMetadata().isReadSeekEfficient()) {
+ throw new RuntimeException(
+ String.format("File has to be seekable: %s", file.getMetadata().resourceId()));
+ }
+ return new BeamParquetInputFile(file.openSeekable());
+ }
+
+ @ProcessElement
+ public void processElement(
+ @Element FileIO.ReadableFile file,
+ RestrictionTracker<OffsetRange, Long> tracker,
+ OutputReceiver<GenericRecord> outputReceiver)
+ throws Exception {
+ ReadSupport<GenericRecord> readSupport;
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ readSupport = new AvroReadSupport<GenericRecord>(model);
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ Filter filter = checkNotNull(options.getRecordFilter(), "filter");
+ conf = ((HadoopReadOptions) options).getConf();
+ for (String property : options.getPropertyNames()) {
+ conf.set(property, options.getProperty(property));
+ }
+ FileMetaData parquetFileMetadata = reader.getFooter().getFileMetaData();
+ MessageType fileSchema = parquetFileMetadata.getSchema();
+ Map<String, String> fileMetadata = parquetFileMetadata.getKeyValueMetaData();
+
+ ReadSupport.ReadContext readContext =
+ readSupport.init(new InitContext(conf, toSetMultiMap(fileMetadata), fileSchema));
+ ColumnIOFactory columnIOFactory = new ColumnIOFactory(parquetFileMetadata.getCreatedBy());
+ MessageType requestedSchema = readContext.getRequestedSchema();
+ RecordMaterializer<GenericRecord> recordConverter =
+ readSupport.prepareForRead(conf, fileMetadata, fileSchema, readContext);
+ boolean strictTypeChecking = options.isEnabled(STRICT_TYPE_CHECKING, true);
+ boolean filterRecords = options.useRecordFilter();
+ reader.setRequestedSchema(requestedSchema);
+ MessageColumnIO columnIO =
+ columnIOFactory.getColumnIO(requestedSchema, fileSchema, strictTypeChecking);
+ long currentBlock = tracker.currentRestriction().getFrom();
+ for (int i = 0; i < currentBlock; i++) {
+ reader.skipNextRowGroup();
+ }
+ while (tracker.tryClaim(currentBlock)) {
+
+ LOG.info("reading block" + currentBlock);
+ PageReadStore pages = reader.readNextRowGroup();
+ currentBlock += 1;
+ RecordReader<GenericRecord> recordReader =
+ columnIO.getRecordReader(
+ pages, recordConverter, filterRecords ? filter : FilterCompat.NOOP);
+ long currentRow = 0;
+ long totalRows = pages.getRowCount();
+ while (currentRow < totalRows) {
+ try {
+ GenericRecord record;
+ currentRow += 1;
+ try {
+ record = recordReader.read();
+ } catch (RecordMaterializer.RecordMaterializationException e) {
+ LOG.debug("skipping a corrupt record");
+ continue;
+ }
+ if (recordReader.shouldSkipCurrentRecord()) {
+ // this record is being filtered via the filter2 package
+ LOG.debug("skipping record");
+ continue;
+ }
+ if (record == null) {
+ // only happens with FilteredRecordReader at end of block
+ LOG.debug("filtered record reader reached end of block");
+ break;
+ }
+ if (tracker instanceof BlockTracker) {
+ ((BlockTracker) tracker).makeProgress();
+ }
+ outputReceiver.output(record);
+ } catch (RuntimeException e) {
+ throw new ParquetDecodingException(
+ format(
+ "Can not read value at %d in block %d in file %s",
+ currentRow, currentBlock, file.toString()),
+ e);
+ }
+ }
+ LOG.info("finish read " + currentRow + " rows");
+ }
+ }
+
+ private Configuration setConf() throws Exception {
+ Configuration conf = new Configuration();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ if (model != null
+ && (model.getClass() == GenericData.class || model.getClass() == SpecificData.class)) {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, true);
+ } else {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, false);
+ }
+ return conf;
+ }
+
+ @GetInitialRestriction
+ public OffsetRange getInitialRestriction(@Element FileIO.ReadableFile file) throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ return new OffsetRange(0, reader.getRowGroups().size());
+ }
+
+ @SplitRestriction
+ public void split(
+ @Restriction OffsetRange restriction,
+ OutputReceiver<OffsetRange> out,
+ @Element FileIO.ReadableFile file)
+ throws Exception {
+ long start = restriction.getFrom();
+ long end = restriction.getFrom();
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ List<BlockMetaData> rowGroups = reader.getRowGroups();
+ long totalSize = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ totalSize += rowGroups.get((int) i).getTotalByteSize();
+ end += 1;
+ if (totalSize > SPLIT_LIMIT) {
+ start = end;
+ totalSize = 0;
+ out.output(new OffsetRange(start, end));
+ }
+ }
+ if (totalSize != 0) {
+ out.output(new OffsetRange(start, end));
+ }
+ }
+
+ @NewTracker
+ public RestrictionTracker<OffsetRange, Long> newTracker(
+ @Restriction OffsetRange restriction, @Element FileIO.ReadableFile file)
+ throws Exception {
+ return new BlockTracker(
+ restriction, (long) getSize(file, restriction), getRecordCount(file, restriction));
+ }
+
+ @GetRestrictionCoder
+ public OffsetRange.Coder getRestrictionCoder() {
+ return new OffsetRange.Coder();
+ }
+
+ public long getRecordCount(
+ @Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ long recordCount = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
Review comment:
How expensive will this be ? Note that input file can be arbitrary long (for example, petabytes) and we don't want the newTracker() call to hang forever. BTW I think we can safely assume that records are of equal size. So if we can more efficiently determine the number of records per block/row group that should be adequate (for example, we do this for Avro).
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
+ return input
+ .apply(ParDo.of(new SplitReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ } else {
+ return input
+ .apply(ParDo.of(new ReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ }
+ }
+
+ @DoFn.BoundedPerElement
+ static class SplitReadFn extends DoFn<FileIO.ReadableFile, GenericRecord> {
+ private Class<? extends GenericData> modelClass;
+ private static final Logger LOG = LoggerFactory.getLogger(SplitReadFn.class);
+ private static final long SPLIT_LIMIT = 64000000;
+ ReadSupport<GenericRecord> readSupport;
+
+ SplitReadFn(GenericData model) {
+ this.modelClass = model != null ? model.getClass() : null;
+ }
+
+ private static <K, V> Map<K, Set<V>> toSetMultiMap(Map<K, V> map) {
+ Map<K, Set<V>> setMultiMap = new HashMap<K, Set<V>>();
+ for (Map.Entry<K, V> entry : map.entrySet()) {
+ Set<V> set = new HashSet<V>();
+ set.add(entry.getValue());
+ setMultiMap.put(entry.getKey(), Collections.unmodifiableSet(set));
+ }
+ return Collections.unmodifiableMap(setMultiMap);
+ }
+
+ private InputFile getInputFile(FileIO.ReadableFile file) throws IOException {
+ if (!file.getMetadata().isReadSeekEfficient()) {
+ throw new RuntimeException(
+ String.format("File has to be seekable: %s", file.getMetadata().resourceId()));
+ }
+ return new BeamParquetInputFile(file.openSeekable());
+ }
+
+ @ProcessElement
+ public void processElement(
+ @Element FileIO.ReadableFile file,
+ RestrictionTracker<OffsetRange, Long> tracker,
+ OutputReceiver<GenericRecord> outputReceiver)
+ throws Exception {
+ ReadSupport<GenericRecord> readSupport;
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ readSupport = new AvroReadSupport<GenericRecord>(model);
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ Filter filter = checkNotNull(options.getRecordFilter(), "filter");
+ conf = ((HadoopReadOptions) options).getConf();
+ for (String property : options.getPropertyNames()) {
+ conf.set(property, options.getProperty(property));
+ }
+ FileMetaData parquetFileMetadata = reader.getFooter().getFileMetaData();
+ MessageType fileSchema = parquetFileMetadata.getSchema();
+ Map<String, String> fileMetadata = parquetFileMetadata.getKeyValueMetaData();
+
+ ReadSupport.ReadContext readContext =
+ readSupport.init(new InitContext(conf, toSetMultiMap(fileMetadata), fileSchema));
+ ColumnIOFactory columnIOFactory = new ColumnIOFactory(parquetFileMetadata.getCreatedBy());
+ MessageType requestedSchema = readContext.getRequestedSchema();
+ RecordMaterializer<GenericRecord> recordConverter =
+ readSupport.prepareForRead(conf, fileMetadata, fileSchema, readContext);
+ boolean strictTypeChecking = options.isEnabled(STRICT_TYPE_CHECKING, true);
+ boolean filterRecords = options.useRecordFilter();
+ reader.setRequestedSchema(requestedSchema);
+ MessageColumnIO columnIO =
+ columnIOFactory.getColumnIO(requestedSchema, fileSchema, strictTypeChecking);
+ long currentBlock = tracker.currentRestriction().getFrom();
+ for (int i = 0; i < currentBlock; i++) {
+ reader.skipNextRowGroup();
+ }
+ while (tracker.tryClaim(currentBlock)) {
+
+ LOG.info("reading block" + currentBlock);
+ PageReadStore pages = reader.readNextRowGroup();
+ currentBlock += 1;
+ RecordReader<GenericRecord> recordReader =
+ columnIO.getRecordReader(
+ pages, recordConverter, filterRecords ? filter : FilterCompat.NOOP);
+ long currentRow = 0;
+ long totalRows = pages.getRowCount();
+ while (currentRow < totalRows) {
+ try {
+ GenericRecord record;
+ currentRow += 1;
+ try {
+ record = recordReader.read();
+ } catch (RecordMaterializer.RecordMaterializationException e) {
+ LOG.debug("skipping a corrupt record");
+ continue;
+ }
+ if (recordReader.shouldSkipCurrentRecord()) {
+ // this record is being filtered via the filter2 package
+ LOG.debug("skipping record");
+ continue;
+ }
+ if (record == null) {
+ // only happens with FilteredRecordReader at end of block
+ LOG.debug("filtered record reader reached end of block");
+ break;
+ }
+ if (tracker instanceof BlockTracker) {
+ ((BlockTracker) tracker).makeProgress();
+ }
+ outputReceiver.output(record);
+ } catch (RuntimeException e) {
+ throw new ParquetDecodingException(
+ format(
+ "Can not read value at %d in block %d in file %s",
+ currentRow, currentBlock, file.toString()),
+ e);
+ }
+ }
+ LOG.info("finish read " + currentRow + " rows");
+ }
+ }
+
+ private Configuration setConf() throws Exception {
+ Configuration conf = new Configuration();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ if (model != null
+ && (model.getClass() == GenericData.class || model.getClass() == SpecificData.class)) {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, true);
+ } else {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, false);
+ }
+ return conf;
+ }
+
+ @GetInitialRestriction
+ public OffsetRange getInitialRestriction(@Element FileIO.ReadableFile file) throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ return new OffsetRange(0, reader.getRowGroups().size());
+ }
+
+ @SplitRestriction
+ public void split(
+ @Restriction OffsetRange restriction,
+ OutputReceiver<OffsetRange> out,
+ @Element FileIO.ReadableFile file)
+ throws Exception {
+ long start = restriction.getFrom();
+ long end = restriction.getFrom();
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ List<BlockMetaData> rowGroups = reader.getRowGroups();
+ long totalSize = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ totalSize += rowGroups.get((int) i).getTotalByteSize();
+ end += 1;
+ if (totalSize > SPLIT_LIMIT) {
+ start = end;
+ totalSize = 0;
+ out.output(new OffsetRange(start, end));
+ }
+ }
+ if (totalSize != 0) {
+ out.output(new OffsetRange(start, end));
+ }
+ }
+
+ @NewTracker
+ public RestrictionTracker<OffsetRange, Long> newTracker(
+ @Restriction OffsetRange restriction, @Element FileIO.ReadableFile file)
+ throws Exception {
+ return new BlockTracker(
+ restriction, (long) getSize(file, restriction), getRecordCount(file, restriction));
+ }
+
+ @GetRestrictionCoder
+ public OffsetRange.Coder getRestrictionCoder() {
+ return new OffsetRange.Coder();
+ }
+
+ public long getRecordCount(
+ @Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ long recordCount = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ recordCount += reader.getRowGroups().get((int) i).getRowCount();
+ }
+ return recordCount;
+ }
+ }
+
+ public double getSize(@Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
Review comment:
If restriction is null that means we'll be reading the whole file. So what we return here should be the size of the file I believe.
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
+ return input
+ .apply(ParDo.of(new SplitReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ } else {
+ return input
+ .apply(ParDo.of(new ReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ }
+ }
+
+ @DoFn.BoundedPerElement
+ static class SplitReadFn extends DoFn<FileIO.ReadableFile, GenericRecord> {
Review comment:
Why do we need a separate DoFn ? We should be able to use the same DoFn but implement SDF specific methods as well (which will also allow us to better reuse code).
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
+ return input
+ .apply(ParDo.of(new SplitReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ } else {
+ return input
+ .apply(ParDo.of(new ReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ }
+ }
+
+ @DoFn.BoundedPerElement
+ static class SplitReadFn extends DoFn<FileIO.ReadableFile, GenericRecord> {
+ private Class<? extends GenericData> modelClass;
+ private static final Logger LOG = LoggerFactory.getLogger(SplitReadFn.class);
+ private static final long SPLIT_LIMIT = 64000000;
+ ReadSupport<GenericRecord> readSupport;
+
+ SplitReadFn(GenericData model) {
+ this.modelClass = model != null ? model.getClass() : null;
+ }
+
+ private static <K, V> Map<K, Set<V>> toSetMultiMap(Map<K, V> map) {
+ Map<K, Set<V>> setMultiMap = new HashMap<K, Set<V>>();
+ for (Map.Entry<K, V> entry : map.entrySet()) {
+ Set<V> set = new HashSet<V>();
+ set.add(entry.getValue());
+ setMultiMap.put(entry.getKey(), Collections.unmodifiableSet(set));
+ }
+ return Collections.unmodifiableMap(setMultiMap);
+ }
+
+ private InputFile getInputFile(FileIO.ReadableFile file) throws IOException {
+ if (!file.getMetadata().isReadSeekEfficient()) {
+ throw new RuntimeException(
+ String.format("File has to be seekable: %s", file.getMetadata().resourceId()));
+ }
+ return new BeamParquetInputFile(file.openSeekable());
+ }
+
+ @ProcessElement
+ public void processElement(
+ @Element FileIO.ReadableFile file,
+ RestrictionTracker<OffsetRange, Long> tracker,
+ OutputReceiver<GenericRecord> outputReceiver)
+ throws Exception {
+ ReadSupport<GenericRecord> readSupport;
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ readSupport = new AvroReadSupport<GenericRecord>(model);
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ Filter filter = checkNotNull(options.getRecordFilter(), "filter");
+ conf = ((HadoopReadOptions) options).getConf();
+ for (String property : options.getPropertyNames()) {
+ conf.set(property, options.getProperty(property));
+ }
+ FileMetaData parquetFileMetadata = reader.getFooter().getFileMetaData();
+ MessageType fileSchema = parquetFileMetadata.getSchema();
+ Map<String, String> fileMetadata = parquetFileMetadata.getKeyValueMetaData();
+
+ ReadSupport.ReadContext readContext =
+ readSupport.init(new InitContext(conf, toSetMultiMap(fileMetadata), fileSchema));
+ ColumnIOFactory columnIOFactory = new ColumnIOFactory(parquetFileMetadata.getCreatedBy());
+ MessageType requestedSchema = readContext.getRequestedSchema();
+ RecordMaterializer<GenericRecord> recordConverter =
+ readSupport.prepareForRead(conf, fileMetadata, fileSchema, readContext);
+ boolean strictTypeChecking = options.isEnabled(STRICT_TYPE_CHECKING, true);
+ boolean filterRecords = options.useRecordFilter();
+ reader.setRequestedSchema(requestedSchema);
+ MessageColumnIO columnIO =
+ columnIOFactory.getColumnIO(requestedSchema, fileSchema, strictTypeChecking);
+ long currentBlock = tracker.currentRestriction().getFrom();
+ for (int i = 0; i < currentBlock; i++) {
+ reader.skipNextRowGroup();
+ }
+ while (tracker.tryClaim(currentBlock)) {
+
+ LOG.info("reading block" + currentBlock);
+ PageReadStore pages = reader.readNextRowGroup();
+ currentBlock += 1;
+ RecordReader<GenericRecord> recordReader =
+ columnIO.getRecordReader(
+ pages, recordConverter, filterRecords ? filter : FilterCompat.NOOP);
+ long currentRow = 0;
+ long totalRows = pages.getRowCount();
+ while (currentRow < totalRows) {
+ try {
+ GenericRecord record;
+ currentRow += 1;
+ try {
+ record = recordReader.read();
+ } catch (RecordMaterializer.RecordMaterializationException e) {
+ LOG.debug("skipping a corrupt record");
+ continue;
+ }
+ if (recordReader.shouldSkipCurrentRecord()) {
+ // this record is being filtered via the filter2 package
+ LOG.debug("skipping record");
+ continue;
+ }
+ if (record == null) {
+ // only happens with FilteredRecordReader at end of block
+ LOG.debug("filtered record reader reached end of block");
+ break;
+ }
+ if (tracker instanceof BlockTracker) {
+ ((BlockTracker) tracker).makeProgress();
Review comment:
Nice!
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
+ return input
+ .apply(ParDo.of(new SplitReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ } else {
+ return input
+ .apply(ParDo.of(new ReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ }
+ }
+
+ @DoFn.BoundedPerElement
+ static class SplitReadFn extends DoFn<FileIO.ReadableFile, GenericRecord> {
+ private Class<? extends GenericData> modelClass;
+ private static final Logger LOG = LoggerFactory.getLogger(SplitReadFn.class);
+ private static final long SPLIT_LIMIT = 64000000;
+ ReadSupport<GenericRecord> readSupport;
+
+ SplitReadFn(GenericData model) {
+ this.modelClass = model != null ? model.getClass() : null;
+ }
+
+ private static <K, V> Map<K, Set<V>> toSetMultiMap(Map<K, V> map) {
+ Map<K, Set<V>> setMultiMap = new HashMap<K, Set<V>>();
+ for (Map.Entry<K, V> entry : map.entrySet()) {
+ Set<V> set = new HashSet<V>();
+ set.add(entry.getValue());
+ setMultiMap.put(entry.getKey(), Collections.unmodifiableSet(set));
+ }
+ return Collections.unmodifiableMap(setMultiMap);
+ }
+
+ private InputFile getInputFile(FileIO.ReadableFile file) throws IOException {
+ if (!file.getMetadata().isReadSeekEfficient()) {
+ throw new RuntimeException(
+ String.format("File has to be seekable: %s", file.getMetadata().resourceId()));
+ }
+ return new BeamParquetInputFile(file.openSeekable());
+ }
+
+ @ProcessElement
+ public void processElement(
+ @Element FileIO.ReadableFile file,
+ RestrictionTracker<OffsetRange, Long> tracker,
+ OutputReceiver<GenericRecord> outputReceiver)
+ throws Exception {
+ ReadSupport<GenericRecord> readSupport;
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ readSupport = new AvroReadSupport<GenericRecord>(model);
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ Filter filter = checkNotNull(options.getRecordFilter(), "filter");
+ conf = ((HadoopReadOptions) options).getConf();
+ for (String property : options.getPropertyNames()) {
+ conf.set(property, options.getProperty(property));
+ }
+ FileMetaData parquetFileMetadata = reader.getFooter().getFileMetaData();
+ MessageType fileSchema = parquetFileMetadata.getSchema();
+ Map<String, String> fileMetadata = parquetFileMetadata.getKeyValueMetaData();
+
+ ReadSupport.ReadContext readContext =
+ readSupport.init(new InitContext(conf, toSetMultiMap(fileMetadata), fileSchema));
+ ColumnIOFactory columnIOFactory = new ColumnIOFactory(parquetFileMetadata.getCreatedBy());
+ MessageType requestedSchema = readContext.getRequestedSchema();
+ RecordMaterializer<GenericRecord> recordConverter =
+ readSupport.prepareForRead(conf, fileMetadata, fileSchema, readContext);
+ boolean strictTypeChecking = options.isEnabled(STRICT_TYPE_CHECKING, true);
+ boolean filterRecords = options.useRecordFilter();
+ reader.setRequestedSchema(requestedSchema);
+ MessageColumnIO columnIO =
+ columnIOFactory.getColumnIO(requestedSchema, fileSchema, strictTypeChecking);
+ long currentBlock = tracker.currentRestriction().getFrom();
+ for (int i = 0; i < currentBlock; i++) {
+ reader.skipNextRowGroup();
+ }
+ while (tracker.tryClaim(currentBlock)) {
+
+ LOG.info("reading block" + currentBlock);
+ PageReadStore pages = reader.readNextRowGroup();
+ currentBlock += 1;
+ RecordReader<GenericRecord> recordReader =
+ columnIO.getRecordReader(
+ pages, recordConverter, filterRecords ? filter : FilterCompat.NOOP);
+ long currentRow = 0;
+ long totalRows = pages.getRowCount();
+ while (currentRow < totalRows) {
+ try {
+ GenericRecord record;
+ currentRow += 1;
+ try {
+ record = recordReader.read();
+ } catch (RecordMaterializer.RecordMaterializationException e) {
+ LOG.debug("skipping a corrupt record");
+ continue;
+ }
+ if (recordReader.shouldSkipCurrentRecord()) {
+ // this record is being filtered via the filter2 package
+ LOG.debug("skipping record");
+ continue;
+ }
+ if (record == null) {
+ // only happens with FilteredRecordReader at end of block
+ LOG.debug("filtered record reader reached end of block");
+ break;
+ }
+ if (tracker instanceof BlockTracker) {
+ ((BlockTracker) tracker).makeProgress();
+ }
+ outputReceiver.output(record);
+ } catch (RuntimeException e) {
+ throw new ParquetDecodingException(
+ format(
+ "Can not read value at %d in block %d in file %s",
+ currentRow, currentBlock, file.toString()),
+ e);
+ }
+ }
+ LOG.info("finish read " + currentRow + " rows");
+ }
+ }
+
+ private Configuration setConf() throws Exception {
+ Configuration conf = new Configuration();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ if (model != null
+ && (model.getClass() == GenericData.class || model.getClass() == SpecificData.class)) {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, true);
+ } else {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, false);
+ }
+ return conf;
+ }
+
+ @GetInitialRestriction
+ public OffsetRange getInitialRestriction(@Element FileIO.ReadableFile file) throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ return new OffsetRange(0, reader.getRowGroups().size());
+ }
+
+ @SplitRestriction
+ public void split(
+ @Restriction OffsetRange restriction,
+ OutputReceiver<OffsetRange> out,
+ @Element FileIO.ReadableFile file)
+ throws Exception {
+ long start = restriction.getFrom();
+ long end = restriction.getFrom();
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ List<BlockMetaData> rowGroups = reader.getRowGroups();
+ long totalSize = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ totalSize += rowGroups.get((int) i).getTotalByteSize();
+ end += 1;
+ if (totalSize > SPLIT_LIMIT) {
+ start = end;
+ totalSize = 0;
+ out.output(new OffsetRange(start, end));
+ }
+ }
+ if (totalSize != 0) {
+ out.output(new OffsetRange(start, end));
+ }
+ }
+
+ @NewTracker
+ public RestrictionTracker<OffsetRange, Long> newTracker(
+ @Restriction OffsetRange restriction, @Element FileIO.ReadableFile file)
+ throws Exception {
+ return new BlockTracker(
+ restriction, (long) getSize(file, restriction), getRecordCount(file, restriction));
+ }
+
+ @GetRestrictionCoder
+ public OffsetRange.Coder getRestrictionCoder() {
+ return new OffsetRange.Coder();
+ }
+
+ public long getRecordCount(
+ @Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ long recordCount = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ recordCount += reader.getRowGroups().get((int) i).getRowCount();
+ }
+ return recordCount;
+ }
+ }
+
+ public double getSize(@Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ double size = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ size += reader.getRowGroups().get((int) i).getTotalByteSize();
Review comment:
How expensive is this operation ?
##########
File path: sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -230,12 +281,271 @@ public ReadFiles withAvroDataModel(GenericData model) {
return toBuilder().setAvroDataModel(model).build();
}
+ public ReadFiles withSplit() {
+ return toBuilder().setSplit(true).build();
+ }
+
@Override
public PCollection<GenericRecord> expand(PCollection<FileIO.ReadableFile> input) {
checkNotNull(getSchema(), "Schema can not be null");
- return input
- .apply(ParDo.of(new ReadFn(getAvroDataModel())))
- .setCoder(AvroCoder.of(getSchema()));
+ if (!getSplit()) {
+ return input
+ .apply(ParDo.of(new SplitReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ } else {
+ return input
+ .apply(ParDo.of(new ReadFn(getAvroDataModel())))
+ .setCoder(AvroCoder.of(getSchema()));
+ }
+ }
+
+ @DoFn.BoundedPerElement
+ static class SplitReadFn extends DoFn<FileIO.ReadableFile, GenericRecord> {
+ private Class<? extends GenericData> modelClass;
+ private static final Logger LOG = LoggerFactory.getLogger(SplitReadFn.class);
+ private static final long SPLIT_LIMIT = 64000000;
+ ReadSupport<GenericRecord> readSupport;
+
+ SplitReadFn(GenericData model) {
+ this.modelClass = model != null ? model.getClass() : null;
+ }
+
+ private static <K, V> Map<K, Set<V>> toSetMultiMap(Map<K, V> map) {
+ Map<K, Set<V>> setMultiMap = new HashMap<K, Set<V>>();
+ for (Map.Entry<K, V> entry : map.entrySet()) {
+ Set<V> set = new HashSet<V>();
+ set.add(entry.getValue());
+ setMultiMap.put(entry.getKey(), Collections.unmodifiableSet(set));
+ }
+ return Collections.unmodifiableMap(setMultiMap);
+ }
+
+ private InputFile getInputFile(FileIO.ReadableFile file) throws IOException {
+ if (!file.getMetadata().isReadSeekEfficient()) {
+ throw new RuntimeException(
+ String.format("File has to be seekable: %s", file.getMetadata().resourceId()));
+ }
+ return new BeamParquetInputFile(file.openSeekable());
+ }
+
+ @ProcessElement
+ public void processElement(
+ @Element FileIO.ReadableFile file,
+ RestrictionTracker<OffsetRange, Long> tracker,
+ OutputReceiver<GenericRecord> outputReceiver)
+ throws Exception {
+ ReadSupport<GenericRecord> readSupport;
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ readSupport = new AvroReadSupport<GenericRecord>(model);
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ Filter filter = checkNotNull(options.getRecordFilter(), "filter");
+ conf = ((HadoopReadOptions) options).getConf();
+ for (String property : options.getPropertyNames()) {
+ conf.set(property, options.getProperty(property));
+ }
+ FileMetaData parquetFileMetadata = reader.getFooter().getFileMetaData();
+ MessageType fileSchema = parquetFileMetadata.getSchema();
+ Map<String, String> fileMetadata = parquetFileMetadata.getKeyValueMetaData();
+
+ ReadSupport.ReadContext readContext =
+ readSupport.init(new InitContext(conf, toSetMultiMap(fileMetadata), fileSchema));
+ ColumnIOFactory columnIOFactory = new ColumnIOFactory(parquetFileMetadata.getCreatedBy());
+ MessageType requestedSchema = readContext.getRequestedSchema();
+ RecordMaterializer<GenericRecord> recordConverter =
+ readSupport.prepareForRead(conf, fileMetadata, fileSchema, readContext);
+ boolean strictTypeChecking = options.isEnabled(STRICT_TYPE_CHECKING, true);
+ boolean filterRecords = options.useRecordFilter();
+ reader.setRequestedSchema(requestedSchema);
+ MessageColumnIO columnIO =
+ columnIOFactory.getColumnIO(requestedSchema, fileSchema, strictTypeChecking);
+ long currentBlock = tracker.currentRestriction().getFrom();
+ for (int i = 0; i < currentBlock; i++) {
+ reader.skipNextRowGroup();
+ }
+ while (tracker.tryClaim(currentBlock)) {
+
+ LOG.info("reading block" + currentBlock);
+ PageReadStore pages = reader.readNextRowGroup();
+ currentBlock += 1;
+ RecordReader<GenericRecord> recordReader =
+ columnIO.getRecordReader(
+ pages, recordConverter, filterRecords ? filter : FilterCompat.NOOP);
+ long currentRow = 0;
+ long totalRows = pages.getRowCount();
+ while (currentRow < totalRows) {
+ try {
+ GenericRecord record;
+ currentRow += 1;
+ try {
+ record = recordReader.read();
+ } catch (RecordMaterializer.RecordMaterializationException e) {
+ LOG.debug("skipping a corrupt record");
+ continue;
+ }
+ if (recordReader.shouldSkipCurrentRecord()) {
+ // this record is being filtered via the filter2 package
+ LOG.debug("skipping record");
+ continue;
+ }
+ if (record == null) {
+ // only happens with FilteredRecordReader at end of block
+ LOG.debug("filtered record reader reached end of block");
+ break;
+ }
+ if (tracker instanceof BlockTracker) {
+ ((BlockTracker) tracker).makeProgress();
+ }
+ outputReceiver.output(record);
+ } catch (RuntimeException e) {
+ throw new ParquetDecodingException(
+ format(
+ "Can not read value at %d in block %d in file %s",
+ currentRow, currentBlock, file.toString()),
+ e);
+ }
+ }
+ LOG.info("finish read " + currentRow + " rows");
+ }
+ }
+
+ private Configuration setConf() throws Exception {
+ Configuration conf = new Configuration();
+ GenericData model = null;
+ if (modelClass != null) {
+ model = (GenericData) modelClass.getMethod("get").invoke(null);
+ }
+ if (model != null
+ && (model.getClass() == GenericData.class || model.getClass() == SpecificData.class)) {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, true);
+ } else {
+ conf.setBoolean(AvroReadSupport.AVRO_COMPATIBILITY, false);
+ }
+ return conf;
+ }
+
+ @GetInitialRestriction
+ public OffsetRange getInitialRestriction(@Element FileIO.ReadableFile file) throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ return new OffsetRange(0, reader.getRowGroups().size());
+ }
+
+ @SplitRestriction
+ public void split(
+ @Restriction OffsetRange restriction,
+ OutputReceiver<OffsetRange> out,
+ @Element FileIO.ReadableFile file)
+ throws Exception {
+ long start = restriction.getFrom();
+ long end = restriction.getFrom();
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ List<BlockMetaData> rowGroups = reader.getRowGroups();
+ long totalSize = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ totalSize += rowGroups.get((int) i).getTotalByteSize();
+ end += 1;
+ if (totalSize > SPLIT_LIMIT) {
+ start = end;
+ totalSize = 0;
+ out.output(new OffsetRange(start, end));
+ }
+ }
+ if (totalSize != 0) {
+ out.output(new OffsetRange(start, end));
+ }
+ }
+
+ @NewTracker
+ public RestrictionTracker<OffsetRange, Long> newTracker(
+ @Restriction OffsetRange restriction, @Element FileIO.ReadableFile file)
+ throws Exception {
+ return new BlockTracker(
+ restriction, (long) getSize(file, restriction), getRecordCount(file, restriction));
+ }
+
+ @GetRestrictionCoder
+ public OffsetRange.Coder getRestrictionCoder() {
+ return new OffsetRange.Coder();
+ }
+
+ public long getRecordCount(
+ @Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ long recordCount = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ recordCount += reader.getRowGroups().get((int) i).getRowCount();
+ }
+ return recordCount;
+ }
+ }
+
+ public double getSize(@Element FileIO.ReadableFile file, @Restriction OffsetRange restriction)
+ throws Exception {
+ InputFile inputFile = getInputFile(file);
+ Configuration conf = setConf();
+ ParquetReadOptions options = HadoopReadOptions.builder(conf).build();
+ ParquetFileReader reader = ParquetFileReader.open(inputFile, options);
+ if (restriction == null) {
+ return 0;
+ } else {
+ double size = 0;
+ for (long i = restriction.getFrom(); i < restriction.getTo(); i++) {
+ size += reader.getRowGroups().get((int) i).getTotalByteSize();
+ }
+ return size;
+ }
+ }
+ }
+
+ private static class BlockTracker extends OffsetRangeTracker {
+ private long totalWork;
+ private long progress;
+ private long recordSize;
+
+ public BlockTracker(OffsetRange range, long totalWork, long recordCount) {
+ super(range);
+ this.recordSize = totalWork / recordCount;
+ this.totalWork = recordSize * recordCount;
Review comment:
this.totalWork = totalWork
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