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Add Parquet Row Group Bloom Filter Support #4831

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e814287
Parquet bloom filter support
huaxingao May 21, 2022
3b985f4
add co-author.
huaxingao May 21, 2022
f0e6aa1
add co-author.
huaxingao May 21, 2022
9c6c64f
address comments and fix filter in TestSparkReaderWithBloomFilter
huaxingao May 24, 2022
0520fb4
update configuration.md to add the bloom filter related properties
huaxingao May 25, 2022
893e7b0
address comments
huaxingao May 29, 2022
7613b9c
fix cast error
huaxingao May 30, 2022
1fabb2d
address comments
huaxingao May 30, 2022
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18 changes: 18 additions & 0 deletions api/src/main/java/org/apache/iceberg/data/Record.java
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Expand Up @@ -58,4 +58,22 @@ default Record copy(String field1, Object value1, String field2, Object value2,
return copy(overwriteValues);
}

default Record copy(String field1, Object value1, String field2, Object value2, String field3, Object value3,
String field4, Object value4, String field5, Object value5, String field6, Object value6,
String field7, Object value7, String field8, Object value8, String field9, Object value9,
String field10, Object value10, String field11, Object value11) {
Map<String, Object> overwriteValues = Maps.newHashMapWithExpectedSize(11);
overwriteValues.put(field1, value1);
overwriteValues.put(field2, value2);
overwriteValues.put(field3, value3);
overwriteValues.put(field4, value4);
overwriteValues.put(field5, value5);
overwriteValues.put(field6, value6);
overwriteValues.put(field7, value7);
overwriteValues.put(field8, value8);
overwriteValues.put(field9, value9);
overwriteValues.put(field10, value10);
overwriteValues.put(field11, value11);
return copy(overwriteValues);
}
}
10 changes: 10 additions & 0 deletions core/src/main/java/org/apache/iceberg/TableProperties.java
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Expand Up @@ -167,6 +167,16 @@ private TableProperties() {
"write.delete.parquet.row-group-check-max-record-count";
public static final int PARQUET_ROW_GROUP_CHECK_MAX_RECORD_COUNT_DEFAULT = 10000;

public static final String DEFAULT_PARQUET_BLOOM_FILTER_ENABLED = "write.parquet.bloom-filter-enabled.default";
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@stevenzwu stevenzwu May 26, 2022

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does it ever make sense to enable bloom filter for all columns? should we only allow bloom filter for explicitly specified columns?

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@huaxingao huaxingao May 26, 2022

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It is not a common usage to enable bloom filter for all columns, but it's legal. This is consistent with the parquet-mr bloom filter implementations.

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@rdblue rdblue May 26, 2022

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I agree with Steven. I think it only makes sense to enable bloom filters for some columns.

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@kbendick kbendick May 26, 2022

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+1. While it's consistent with the parquet-mr bloom filter implementaiton, we need to think of user experience first and foremost.

It doesn't make sense to enable bloom filters for a lot of columns. And many users don't do any tuning of their metadata / statistics.

I think it's in-line with other things we do to make the users experience better, like turning off column level statistics after a certain number of columns. We can point it out in the docs under a big !!!NOTE (that's highlighted) that bloom filter is only used when turned on.

It's really an advanced thing to use at all imo.

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@huaxingao huaxingao May 30, 2022

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Sounds good. I have removed DEFAULT_PARQUET_BLOOM_FILTER_ENABLED. Now user needs to enable bloom filter for individual column using PARQUET_BLOOM_FILTER_COLUMN_ENABLED_PREFIX. If the column is a complex type, user needs to enable the column inside the complex type, for example,
set(PARQUET_BLOOM_FILTER_COLUMN_ENABLED_PREFIX + "struct_col.int_field", "true")

public static final boolean DEFAULT_PARQUET_BLOOM_FILTER_ENABLED_DEFAULT = false;

public static final String PARQUET_BLOOM_FILTER_COLUMN_ENABLED_PREFIX = "write.parquet.bloom-filter-enabled.column.";
public static final String PARQUET_BLOOM_FILTER_COLUMN_EXPECTED_NDV_PREFIX =
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@chenjunjiedada chenjunjiedada May 25, 2022

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It would be better to document that the NDV is specific for a parquet file.

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@huaxingao huaxingao May 25, 2022

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Thank for your comment. I documented this in configuration.md.

"write.parquet.bloom-filter-expected-ndv.column.";

public static final String PARQUET_BLOOM_FILTER_MAX_BYTES = "write.parquet.bloom-filter-max-bytes";
public static final int PARQUET_BLOOM_FILTER_MAX_BYTES_DEFAULT = 1024 * 1024;

public static final String AVRO_COMPRESSION = "write.avro.compression-codec";
public static final String DELETE_AVRO_COMPRESSION = "write.delete.avro.compression-codec";
public static final String AVRO_COMPRESSION_DEFAULT = "gzip";
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13 changes: 13 additions & 0 deletions data/src/test/java/org/apache/iceberg/data/FileHelpers.java
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Expand Up @@ -42,9 +42,14 @@
import org.apache.iceberg.types.Types;
import org.apache.iceberg.util.CharSequenceSet;
import org.apache.iceberg.util.Pair;
import org.apache.iceberg.util.PropertyUtil;

import static org.apache.iceberg.TableProperties.DEFAULT_FILE_FORMAT;
import static org.apache.iceberg.TableProperties.DEFAULT_FILE_FORMAT_DEFAULT;
import static org.apache.iceberg.TableProperties.DEFAULT_PARQUET_BLOOM_FILTER_ENABLED;
import static org.apache.iceberg.TableProperties.DEFAULT_PARQUET_BLOOM_FILTER_ENABLED_DEFAULT;
import static org.apache.iceberg.TableProperties.PARQUET_ROW_GROUP_SIZE_BYTES;
import static org.apache.iceberg.TableProperties.PARQUET_ROW_GROUP_SIZE_BYTES_DEFAULT;

public class FileHelpers {
private FileHelpers() {
Expand Down Expand Up @@ -115,6 +120,14 @@ public static DataFile writeDataFile(Table table, OutputFile out, StructLike par
throws IOException {
FileFormat format = defaultFormat(table.properties());
GenericAppenderFactory factory = new GenericAppenderFactory(table.schema(), table.spec());
boolean useBloomFilter = PropertyUtil.propertyAsBoolean(table.properties(),
DEFAULT_PARQUET_BLOOM_FILTER_ENABLED,
DEFAULT_PARQUET_BLOOM_FILTER_ENABLED_DEFAULT);
int blockSize = PropertyUtil.propertyAsInt(table.properties(),
PARQUET_ROW_GROUP_SIZE_BYTES,
PARQUET_ROW_GROUP_SIZE_BYTES_DEFAULT);
factory.set(DEFAULT_PARQUET_BLOOM_FILTER_ENABLED, Boolean.toString(useBloomFilter));
factory.set(PARQUET_ROW_GROUP_SIZE_BYTES, Integer.toString(blockSize));

FileAppender<Record> writer = factory.newAppender(out, format);
try (Closeable toClose = writer) {
Expand Down
4 changes: 4 additions & 0 deletions docs/tables/configuration.md
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Expand Up @@ -50,6 +50,10 @@ Iceberg tables support table properties to configure table behavior, like the de
| write.parquet.dict-size-bytes | 2097152 (2 MB) | Parquet dictionary page size |
| write.parquet.compression-codec | gzip | Parquet compression codec: zstd, brotli, lz4, gzip, snappy, uncompressed |
| write.parquet.compression-level | null | Parquet compression level |
| write.parquet.bloom-filter-enabled.default | false | Whether to enable writing bloom filter for all columns |
| write.parquet.bloom-filter-enabled.column.col1 | (not set) | Whether to enable writing bloom filter for column 'col1' to allow per-column configuration; This property overrides `bloom-filter-enabled.default` for the specified column; For example, setting both `write.parquet.bloom-filter-enabled.default=true` and `write.parquet.bloom-filter-enabled.column.some_col=false` will enable bloom filter for all columns except `some_col` |
| write.parquet.bloom-filter-expected-ndv.column.col1 | (not set) | The expected number of distinct values in a column, it is used to compute the optimal size of the bloom filter; Note that the NDV is specific for a parquet file. If this property is not set, the bloom filter will use the maximum size set in `bloom-filter-max-bytes`; If this property is set for a column, then no need to enable the bloom filter with `write.parquet.bloom-filter-enabled` property |
| write.parquet.bloom-filter-max-bytes | 1048576 (1 MB) | The maximum number of bytes for a bloom filter bitset |
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@rdblue rdblue May 26, 2022

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What is the behavior of this? If the NDV requires a size that is too large, does it skip writing the bloom filter?

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@huaxingao huaxingao May 30, 2022

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If the NDV requires a size that is too large, parquet still writes the bloom filter using the max bytes set by this property, not using the bitset calculated by NDV.

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@rdblue rdblue May 30, 2022

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I guess there probably isn't much we can do about this, although that behavior makes no sense to me. Is it possible to set the expected false positive probability anywhere? Or is that hard-coded in the Parquet library?

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@huaxingao huaxingao May 30, 2022

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There isn't a property to set fpp in Parquet.

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@rdblue rdblue May 30, 2022

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What fpp is used by Parquet?

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@huaxingao huaxingao May 31, 2022

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Parquet uses 0.01 for fpp.
I chatted offline with @chenjunjiedada, we can probably add a config for fpp in parquet first, and then in iceberg.

| write.avro.compression-codec | gzip | Avro compression codec: gzip(deflate with 9 level), zstd, snappy, uncompressed |
| write.avro.compression-level | null | Avro compression level |
| write.orc.stripe-size-bytes | 67108864 (64 MB) | Define the default ORC stripe size, in bytes |
Expand Down
123 changes: 116 additions & 7 deletions parquet/src/main/java/org/apache/iceberg/parquet/Parquet.java
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Expand Up @@ -78,13 +78,19 @@
import org.apache.parquet.hadoop.metadata.CompressionCodecName;
import org.apache.parquet.schema.MessageType;

import static org.apache.iceberg.TableProperties.DEFAULT_PARQUET_BLOOM_FILTER_ENABLED;
import static org.apache.iceberg.TableProperties.DEFAULT_PARQUET_BLOOM_FILTER_ENABLED_DEFAULT;
import static org.apache.iceberg.TableProperties.DELETE_PARQUET_COMPRESSION;
import static org.apache.iceberg.TableProperties.DELETE_PARQUET_COMPRESSION_LEVEL;
import static org.apache.iceberg.TableProperties.DELETE_PARQUET_DICT_SIZE_BYTES;
import static org.apache.iceberg.TableProperties.DELETE_PARQUET_PAGE_SIZE_BYTES;
import static org.apache.iceberg.TableProperties.DELETE_PARQUET_ROW_GROUP_CHECK_MAX_RECORD_COUNT;
import static org.apache.iceberg.TableProperties.DELETE_PARQUET_ROW_GROUP_CHECK_MIN_RECORD_COUNT;
import static org.apache.iceberg.TableProperties.DELETE_PARQUET_ROW_GROUP_SIZE_BYTES;
import static org.apache.iceberg.TableProperties.PARQUET_BLOOM_FILTER_COLUMN_ENABLED_PREFIX;
import static org.apache.iceberg.TableProperties.PARQUET_BLOOM_FILTER_COLUMN_EXPECTED_NDV_PREFIX;
import static org.apache.iceberg.TableProperties.PARQUET_BLOOM_FILTER_MAX_BYTES;
import static org.apache.iceberg.TableProperties.PARQUET_BLOOM_FILTER_MAX_BYTES_DEFAULT;
import static org.apache.iceberg.TableProperties.PARQUET_COMPRESSION;
import static org.apache.iceberg.TableProperties.PARQUET_COMPRESSION_DEFAULT;
import static org.apache.iceberg.TableProperties.PARQUET_COMPRESSION_LEVEL;
Expand Down Expand Up @@ -239,6 +245,10 @@ public <D> FileAppender<D> build() throws IOException {
CompressionCodecName codec = context.codec();
int rowGroupCheckMinRecordCount = context.rowGroupCheckMinRecordCount();
int rowGroupCheckMaxRecordCount = context.rowGroupCheckMaxRecordCount();
boolean bloomFilterEnabled = context.bloomFilterEnabled();
int bloomFilterMaxBytes = context.bloomFilterMaxBytes();
Map<String, String> columnBloomFilterEnabled = context.columnBloomFilterEnabled();
Map<String, String> columnBloomFilterNDVs = context.columnBloomFilterNDVs();

if (compressionLevel != null) {
switch (codec) {
Expand Down Expand Up @@ -269,19 +279,34 @@ public <D> FileAppender<D> build() throws IOException {
conf.set(entry.getKey(), entry.getValue());
}

ParquetProperties parquetProperties = ParquetProperties.builder()
ParquetProperties.Builder propsBuilder = ParquetProperties.builder()
.withWriterVersion(writerVersion)
.withPageSize(pageSize)
.withDictionaryPageSize(dictionaryPageSize)
.withMinRowCountForPageSizeCheck(rowGroupCheckMinRecordCount)
.withMaxRowCountForPageSizeCheck(rowGroupCheckMaxRecordCount)
.build();
.withMaxBloomFilterBytes(bloomFilterMaxBytes)
.withBloomFilterEnabled(bloomFilterEnabled);

for (Map.Entry<String, String> entry : columnBloomFilterEnabled.entrySet()) {
String colPath = entry.getKey();
String bloomEnabled = entry.getValue();
propsBuilder.withBloomFilterEnabled(colPath, Boolean.valueOf(bloomEnabled));
}

for (Map.Entry<String, String> entry : columnBloomFilterNDVs.entrySet()) {
String colPath = entry.getKey();
String numDistinctValue = entry.getValue();
propsBuilder.withBloomFilterNDV(colPath, Long.valueOf(numDistinctValue));
}

ParquetProperties parquetProperties = propsBuilder.build();

return new org.apache.iceberg.parquet.ParquetWriter<>(
conf, file, schema, rowGroupSize, metadata, createWriterFunc, codec,
parquetProperties, metricsConfig, writeMode);
} else {
return new ParquetWriteAdapter<>(new ParquetWriteBuilder<D>(ParquetIO.file(file))
ParquetWriteBuilder<D> parquetWriteBuilder = new ParquetWriteBuilder<D>(ParquetIO.file(file))
.withWriterVersion(writerVersion)
.setType(type)
.setConfig(config)
Expand All @@ -292,11 +317,39 @@ public <D> FileAppender<D> build() throws IOException {
.withRowGroupSize(rowGroupSize)
.withPageSize(pageSize)
.withDictionaryPageSize(dictionaryPageSize)
.build(),
// TODO: add .withMaxBloomFilterBytes(bloomFilterMaxBytes) once ParquetWriter.Builder supports it
.withBloomFilterEnabled(bloomFilterEnabled);

for (Map.Entry<String, String> entry : columnBloomFilterEnabled.entrySet()) {
String colPath = entry.getKey();
String bloomEnabled = entry.getValue();
parquetWriteBuilder.withBloomFilterEnabled(colPath, Boolean.valueOf(bloomEnabled));
}

for (Map.Entry<String, String> entry : columnBloomFilterNDVs.entrySet()) {
String colPath = entry.getKey();
String numDistinctValue = entry.getValue();
parquetWriteBuilder.withBloomFilterNDV(colPath, Long.valueOf(numDistinctValue));
}

return new ParquetWriteAdapter<>(
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@rdblue rdblue May 26, 2022

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@aokolnychyi, what do you think about removing the old ParquetWriteAdapter code? I don't think that anyone uses it anymore.

parquetWriteBuilder.build(),
metricsConfig);
}
}

private static Map<String, String> getBloomColumnConfigMap(String prefix, Map<String, String> config) {
Map<String, String> columnBloomFilterConfig = Maps.newHashMap();
config.keySet().stream()
.filter(key -> key.startsWith(prefix))
.forEach(key -> {
String columnPath = key.replaceFirst(prefix, "");
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@rdblue rdblue May 30, 2022

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Since this uses column name in the config, is there any logic to update these configs when columns are renamed?

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@huaxingao huaxingao May 30, 2022

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Good question. I don't have a logic to update the configs when columns are renamed. I think we are OK, though. At write path, I use these configs to write bloom filters at file creation time. I don't use these configs any more for read. At read path, the bloom filters are loaded using id instead of column name. If the columns are renamed after the bloom filters have been written, as long as the id are still the same, the bloom filters should be able to loaded OK.

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@rdblue rdblue May 30, 2022

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We're okay for adding read support, but we should consider how to configure write support then.

String bloomFilterMode = config.get(key);
columnBloomFilterConfig.put(columnPath, bloomFilterMode);
});
return columnBloomFilterConfig;
}

private static class Context {
private final int rowGroupSize;
private final int pageSize;
Expand All @@ -305,17 +358,27 @@ private static class Context {
private final String compressionLevel;
private final int rowGroupCheckMinRecordCount;
private final int rowGroupCheckMaxRecordCount;
private final boolean bloomFilterEnabled;
private final int bloomFilterMaxBytes;
private final Map<String, String> columnBloomFilterEnabled;
private final Map<String, String> columnBloomFilterNDVs;

private Context(int rowGroupSize, int pageSize, int dictionaryPageSize,
CompressionCodecName codec, String compressionLevel,
int rowGroupCheckMinRecordCount, int rowGroupCheckMaxRecordCount) {
int rowGroupCheckMinRecordCount, int rowGroupCheckMaxRecordCount,
boolean bloomFilterEnabled, int bloomFilterMaxBytes,
Map<String, String> columnBloomFilterEnabled, Map<String, String> columnBloomFilterNDVs) {
this.rowGroupSize = rowGroupSize;
this.pageSize = pageSize;
this.dictionaryPageSize = dictionaryPageSize;
this.codec = codec;
this.compressionLevel = compressionLevel;
this.rowGroupCheckMinRecordCount = rowGroupCheckMinRecordCount;
this.rowGroupCheckMaxRecordCount = rowGroupCheckMaxRecordCount;
this.bloomFilterEnabled = bloomFilterEnabled;
this.bloomFilterMaxBytes = bloomFilterMaxBytes;
this.columnBloomFilterEnabled = columnBloomFilterEnabled;
this.columnBloomFilterNDVs = columnBloomFilterNDVs;
}

static Context dataContext(Map<String, String> config) {
Expand Down Expand Up @@ -348,8 +411,22 @@ static Context dataContext(Map<String, String> config) {
Preconditions.checkArgument(rowGroupCheckMaxRecordCount >= rowGroupCheckMinRecordCount,
"Row group check maximum record count must be >= minimal record count");

boolean bloomFilterEnabled = PropertyUtil.propertyAsBoolean(config, DEFAULT_PARQUET_BLOOM_FILTER_ENABLED,
DEFAULT_PARQUET_BLOOM_FILTER_ENABLED_DEFAULT);

int bloomFilterMaxBytes = PropertyUtil.propertyAsInt(config, PARQUET_BLOOM_FILTER_MAX_BYTES,
PARQUET_BLOOM_FILTER_MAX_BYTES_DEFAULT);
Preconditions.checkArgument(bloomFilterMaxBytes > 0, "bloom Filter Max Bytes must be > 0");

Map<String, String> columnBloomFilterEnabled =
getBloomColumnConfigMap(PARQUET_BLOOM_FILTER_COLUMN_ENABLED_PREFIX, config);

Map<String, String> columnBloomFilterNDVs =
getBloomColumnConfigMap(PARQUET_BLOOM_FILTER_COLUMN_EXPECTED_NDV_PREFIX, config);

return new Context(rowGroupSize, pageSize, dictionaryPageSize, codec, compressionLevel,
rowGroupCheckMinRecordCount, rowGroupCheckMaxRecordCount);
rowGroupCheckMinRecordCount, rowGroupCheckMaxRecordCount, bloomFilterEnabled, bloomFilterMaxBytes,
columnBloomFilterEnabled, columnBloomFilterNDVs);
}

static Context deleteContext(Map<String, String> config) {
Expand Down Expand Up @@ -385,8 +462,22 @@ static Context deleteContext(Map<String, String> config) {
Preconditions.checkArgument(rowGroupCheckMaxRecordCount >= rowGroupCheckMinRecordCount,
"Row group check maximum record count must be >= minimal record count");

boolean bloomFilterEnabled = PropertyUtil.propertyAsBoolean(config, DEFAULT_PARQUET_BLOOM_FILTER_ENABLED,
DEFAULT_PARQUET_BLOOM_FILTER_ENABLED_DEFAULT);

int bloomFilterMaxBytes = PropertyUtil.propertyAsInt(config, PARQUET_BLOOM_FILTER_MAX_BYTES,
PARQUET_BLOOM_FILTER_MAX_BYTES_DEFAULT);
Preconditions.checkArgument(bloomFilterMaxBytes > 0, "bloom Filter Max Bytes must be > 0");

Map<String, String> columnBloomFilterEnabled =
getBloomColumnConfigMap(PARQUET_BLOOM_FILTER_COLUMN_ENABLED_PREFIX, config);

Map<String, String> columnBloomFilterNDVs =
getBloomColumnConfigMap(PARQUET_BLOOM_FILTER_COLUMN_EXPECTED_NDV_PREFIX, config);

return new Context(rowGroupSize, pageSize, dictionaryPageSize, codec, compressionLevel,
rowGroupCheckMinRecordCount, rowGroupCheckMaxRecordCount);
rowGroupCheckMinRecordCount, rowGroupCheckMaxRecordCount, bloomFilterEnabled, bloomFilterMaxBytes,
columnBloomFilterEnabled, columnBloomFilterNDVs);
}

private static CompressionCodecName toCodec(String codecAsString) {
Expand Down Expand Up @@ -424,6 +515,22 @@ int rowGroupCheckMinRecordCount() {
int rowGroupCheckMaxRecordCount() {
return rowGroupCheckMaxRecordCount;
}

boolean bloomFilterEnabled() {
return bloomFilterEnabled;
}

int bloomFilterMaxBytes() {
return bloomFilterMaxBytes;
}

Map<String, String> columnBloomFilterEnabled() {
return columnBloomFilterEnabled;
}

Map<String, String> columnBloomFilterNDVs() {
return columnBloomFilterNDVs;
}
}
}

Expand Down Expand Up @@ -903,12 +1010,14 @@ public <D> CloseableIterable<D> build() {
Schema fileSchema = ParquetSchemaUtil.convert(type);
builder.useStatsFilter()
.useDictionaryFilter()
.useBloomFilter()
.useRecordFilter(filterRecords)
.withFilter(ParquetFilters.convert(fileSchema, filter, caseSensitive));
} else {
// turn off filtering
builder.useStatsFilter(false)
.useDictionaryFilter(false)
.useBloomFilter(false)
.useRecordFilter(false);
}

Expand Down
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