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11 changes: 10 additions & 1 deletion api/src/main/java/org/apache/iceberg/expressions/Binder.java
Original file line number Diff line number Diff line change
Expand Up @@ -91,12 +91,21 @@ static Expression bind(StructType struct,
}

public static Set<Integer> boundReferences(StructType struct, List<Expression> exprs, boolean caseSensitive) {
return references(struct, exprs, caseSensitive, false);
}

public static Set<Integer> references(
StructType struct, List<Expression> exprs, boolean caseSensitive, boolean alreadyBound) {

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Can we detect that an expression is unbound? Maybe identify named refs and return? Then we could just use one method for everything.

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Can i just use instanceof Unbound to detect if an expression is unbound? Something like this:

  private static boolean isUnbound(Expression expr) {
    switch (expr.op()) {
      case TRUE:
        return false;
      case FALSE:
        return false;
      case NOT:
        Not not = (Not) expr;
        return isUnbound(not.child());
      case AND:
        And and = (And) expr;
        return isUnbound(and.left()) || isUnbound(and.right());
      case OR:
        Or or = (Or) expr;
        return isUnbound(or.left()) || isUnbound(or.right());
      default:
        return expr instanceof Unbound;
    }
  }

Then the method boundReferences can be

  public static Set<Integer> boundReferences(StructType struct, List<Expression> exprs, boolean caseSensitive) {
    if (exprs == null) {
      return ImmutableSet.of();
    }
    ReferenceVisitor visitor = new ReferenceVisitor();
    for (Expression expr : exprs) {
      if (isUnbound(expr)) {
        ExpressionVisitors.visit(bind(struct, expr, caseSensitive), visitor);
      } else {
        ExpressionVisitors.visit(expr, visitor);
      }
    }
    return visitor.references;
  }

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Not all expressions are bound or unbound. What about just trying to bind the expression and catching the exception that is thrown if it's already bound? Then you can just move on and return the references.

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Sounds good to me!

if (exprs == null) {
return ImmutableSet.of();
}
ReferenceVisitor visitor = new ReferenceVisitor();
for (Expression expr : exprs) {
ExpressionVisitors.visit(bind(struct, expr, caseSensitive), visitor);
if (!alreadyBound) {
ExpressionVisitors.visit(bind(struct, expr, caseSensitive), visitor);
} else {
ExpressionVisitors.visit(expr, visitor);
}
}
return visitor.references;
}
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Original file line number Diff line number Diff line change
@@ -0,0 +1,331 @@
/*
* 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.iceberg.parquet;

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Is it possible to include the unit test in this PR? I think all you'd need to do is configure the bloom filter settings using the Parquet settings in a Hadoop Configuration rather than through the Iceberg write settings.

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I tried to config using ParquetOutputFormat.BLOOM_FILTER_ENABLED by replacing this line with .set(ParquetOutputFormat.BLOOM_FILTER_ENABLED + "#_id", "true") , but it doesn't work.

Seems Iceberg only honors the Iceberg's properties (which are set by Context at here), but it doesn't really take the properties set by Parquet.

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I think that properties will be passed through to the Hadoop Configuration automatically. Is that no longer true?

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@rdblue Thanks for your quick reply!

Seems the properties need to be passed to InternalParquetRecordWriter through this encodingProps. We need to call the withXXX method explicitly e.g. withDictionaryPageSize to set the property to encodingPropsBuilder

So it seems to me that we have to call this withBloomFilterEnabled explicitly to set the bloom filter property toencodingPropsBuilder. Otherwise, Parquet's InternalParquetRecordWriter won't be able to take it.

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Should I set the Parquet properties to encodingPropsBuilder? If the same properties is also set by iceberg properties, I will reset to overwrite.

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I see. Is it possible to get some tests working without the write-side changes? Maybe write a Parquet file directly and use name mapping? If not then let's try to make the minimal write-side changes to get the test in.

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I made some minimal write-side changes to get the test in. Hope this is OK.


import java.math.BigDecimal;
import java.nio.ByteBuffer;
import java.util.Map;
import java.util.Set;
import java.util.UUID;
import org.apache.iceberg.Schema;
import org.apache.iceberg.expressions.Binder;
import org.apache.iceberg.expressions.BoundReference;
import org.apache.iceberg.expressions.Expression;
import org.apache.iceberg.expressions.ExpressionVisitors;
import org.apache.iceberg.expressions.ExpressionVisitors.BoundExpressionVisitor;
import org.apache.iceberg.expressions.Expressions;
import org.apache.iceberg.expressions.Literal;
import org.apache.iceberg.relocated.com.google.common.collect.ImmutableList;
import org.apache.iceberg.relocated.com.google.common.collect.Maps;
import org.apache.iceberg.relocated.com.google.common.collect.Sets;
import org.apache.iceberg.types.Type;
import org.apache.iceberg.types.TypeUtil;
import org.apache.iceberg.types.Types.StructType;
import org.apache.iceberg.util.DecimalUtil;
import org.apache.iceberg.util.UUIDUtil;
import org.apache.parquet.column.values.bloomfilter.BloomFilter;
import org.apache.parquet.hadoop.BloomFilterReader;
import org.apache.parquet.hadoop.metadata.BlockMetaData;
import org.apache.parquet.hadoop.metadata.ColumnChunkMetaData;
import org.apache.parquet.io.api.Binary;
import org.apache.parquet.schema.DecimalMetadata;
import org.apache.parquet.schema.MessageType;
import org.apache.parquet.schema.PrimitiveType;

public class ParquetBloomRowGroupFilter {
private final Schema schema;
private final Expression expr;
private final boolean caseSensitive;

public ParquetBloomRowGroupFilter(Schema schema, Expression unbound) {
this(schema, unbound, true);
}

public ParquetBloomRowGroupFilter(Schema schema, Expression unbound, boolean caseSensitive) {
this.schema = schema;
StructType struct = schema.asStruct();
this.expr = Binder.bind(struct, Expressions.rewriteNot(unbound), caseSensitive);
this.caseSensitive = caseSensitive;
}

/**
* Tests whether the bloom for a row group may contain records that match the expression.
*
* @param fileSchema schema for the Parquet file
* @param bloomReader a bloom filter reader
* @return false if the file cannot contain rows that match the expression, true otherwise.
*/
public boolean shouldRead(MessageType fileSchema, BlockMetaData rowGroup,
BloomFilterReader bloomReader) {

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Style nit: the starting point of all argument lines should be aligned. That can be at 2 indents from the start of the method OR after the opening ( to start method arguments. There should not be two different indentation levels like you have here (both after ( and 2 indents from the method definition line).

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Thanks for the reminder. I will pay attention to the style next time.

return new BloomEvalVisitor().eval(fileSchema, rowGroup, bloomReader);
}

private static final boolean ROWS_MIGHT_MATCH = true;
private static final boolean ROWS_CANNOT_MATCH = false;

private class BloomEvalVisitor extends BoundExpressionVisitor<Boolean> {
private BloomFilterReader bloomReader;
private Set<Integer> fieldsWithBloomFilter = null;
private Map<Integer, ColumnChunkMetaData> columnMetaMap = null;
private Map<Integer, BloomFilter> bloomCache = null;
private Map<Integer, PrimitiveType> parquetPrimitiveTypes = null;
private Map<Integer, Type> types = null;

private boolean eval(MessageType fileSchema, BlockMetaData rowGroup, BloomFilterReader bloomFilterReader) {
this.bloomReader = bloomFilterReader;
this.fieldsWithBloomFilter = Sets.newHashSet();
this.columnMetaMap = Maps.newHashMap();
this.bloomCache = Maps.newHashMap();
this.parquetPrimitiveTypes = Maps.newHashMap();
this.types = Maps.newHashMap();

for (ColumnChunkMetaData meta : rowGroup.getColumns()) {
PrimitiveType colType = fileSchema.getType(meta.getPath().toArray()).asPrimitiveType();
if (colType.getId() != null) {
int id = colType.getId().intValue();
Type icebergType = schema.findType(id);
if (!ParquetUtil.hasNoBloomFilterPages(meta)) {
fieldsWithBloomFilter.add(id);
}
columnMetaMap.put(id, meta);
parquetPrimitiveTypes.put(id, colType);
types.put(id, icebergType);
}
}

Set<Integer> filterRefs = Binder.references(schema.asStruct(), ImmutableList.of(expr), caseSensitive, true);
// If the filter's column set doesn't overlap with any bloom filter columns, exit early with ROWS_MIGHT_MATCH
if (filterRefs.size() > 0 && Sets.intersection(fieldsWithBloomFilter, filterRefs).isEmpty()) {
return ROWS_MIGHT_MATCH;
}

return ExpressionVisitors.visitEvaluator(expr, this);
}

@Override
public Boolean alwaysTrue() {
return ROWS_MIGHT_MATCH; // all rows match
}

@Override
public Boolean alwaysFalse() {
return ROWS_CANNOT_MATCH; // all rows fail
}

@Override
public Boolean not(Boolean result) {
// not() should be rewritten by RewriteNot
// bloom filter is based on hash and cannot eliminate based on not
throw new UnsupportedOperationException("This path shouldn't be reached.");
}

@Override
public Boolean and(Boolean leftResult, Boolean rightResult) {
return leftResult && rightResult;
}

@Override
public Boolean or(Boolean leftResult, Boolean rightResult) {
return leftResult || rightResult;
}

@Override
public <T> Boolean isNull(BoundReference<T> ref) {
// bloom filter only contain non-nulls and cannot eliminate based on isNull or NotNull
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean notNull(BoundReference<T> ref) {
// bloom filter only contain non-nulls and cannot eliminate based on isNull or NotNull
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean isNaN(BoundReference<T> ref) {
// bloom filter is based on hash and cannot eliminate based on isNaN or notNaN
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean notNaN(BoundReference<T> ref) {
// bloom filter is based on hash and cannot eliminate based on isNaN or notNaN
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean lt(BoundReference<T> ref, Literal<T> lit) {
// bloom filter is based on hash and cannot eliminate based on lt or ltEq or gt or gtEq
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean ltEq(BoundReference<T> ref, Literal<T> lit) {
// bloom filter is based on hash and cannot eliminate based on lt or ltEq or gt or gtEq
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean gt(BoundReference<T> ref, Literal<T> lit) {
// bloom filter is based on hash and cannot eliminate based on lt or ltEq or gt or gtEq
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean gtEq(BoundReference<T> ref, Literal<T> lit) {
// bloom filter is based on hash and cannot eliminate based on lt or ltEq or gt or gtEq
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean eq(BoundReference<T> ref, Literal<T> lit) {
int id = ref.fieldId();
if (!fieldsWithBloomFilter.contains(id)) { // no bloom filter
return ROWS_MIGHT_MATCH;
}

BloomFilter bloom = loadBloomFilter(id);
Type type = types.get(id);
T value = lit.value();
return shouldRead(parquetPrimitiveTypes.get(id), value, bloom, type);
}

@Override
public <T> Boolean notEq(BoundReference<T> ref, Literal<T> lit) {
// bloom filter is based on hash and cannot eliminate based on notEq
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean in(BoundReference<T> ref, Set<T> literalSet) {
int id = ref.fieldId();
if (!fieldsWithBloomFilter.contains(id)) { // no bloom filter
return ROWS_MIGHT_MATCH;
}
BloomFilter bloom = loadBloomFilter(id);
Type type = types.get(id);
for (T e : literalSet) {
if (shouldRead(parquetPrimitiveTypes.get(id), e, bloom, type)) {
return ROWS_MIGHT_MATCH;
}
}
return ROWS_CANNOT_MATCH;
}

@Override
public <T> Boolean notIn(BoundReference<T> ref, Set<T> literalSet) {
// bloom filter is based on hash and cannot eliminate based on notIn
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean startsWith(BoundReference<T> ref, Literal<T> lit) {
// bloom filter is based on hash and cannot eliminate based on startsWith
return ROWS_MIGHT_MATCH;
}

@Override
public <T> Boolean notStartsWith(BoundReference<T> ref, Literal<T> lit) {
// bloom filter is based on hash and cannot eliminate based on startsWith
return ROWS_MIGHT_MATCH;
}

private BloomFilter loadBloomFilter(int id) {
if (bloomCache.containsKey(id)) {
return bloomCache.get(id);
} else {
ColumnChunkMetaData columnChunkMetaData = columnMetaMap.get(id);
BloomFilter bloomFilter = bloomReader.readBloomFilter(columnChunkMetaData);
if (bloomFilter == null) {
throw new IllegalStateException("Failed to read required bloom filter for id: " + id);
} else {
bloomCache.put(id, bloomFilter);
}

return bloomFilter;
}
}

private <T> boolean shouldRead(PrimitiveType primitiveType, T value, BloomFilter bloom, Type type) {
long hashValue = 0;
switch (primitiveType.getPrimitiveTypeName()) {
case INT32:
switch (type.typeId()) {
case DECIMAL:
BigDecimal decimalValue = (BigDecimal) value;
hashValue = bloom.hash(decimalValue.unscaledValue().intValue());
return bloom.findHash(hashValue);
case INTEGER:
case DATE:
hashValue = bloom.hash(((Number) value).intValue());
return bloom.findHash(hashValue);
default:
return ROWS_MIGHT_MATCH;
}
case INT64:
switch (type.typeId()) {
case DECIMAL:
BigDecimal decimalValue = (BigDecimal) value;
hashValue = bloom.hash(decimalValue.unscaledValue().longValue());
return bloom.findHash(hashValue);
case LONG:
case TIME:
case TIMESTAMP:
hashValue = bloom.hash(((Number) value).longValue());
return bloom.findHash(hashValue);
default:
return ROWS_MIGHT_MATCH;
}
case FLOAT:
hashValue = bloom.hash(((Number) value).floatValue());
return bloom.findHash(hashValue);
case DOUBLE:
hashValue = bloom.hash(((Number) value).doubleValue());
return bloom.findHash(hashValue);
case FIXED_LEN_BYTE_ARRAY:
case BINARY:
switch (type.typeId()) {
case STRING:
hashValue = bloom.hash(Binary.fromCharSequence((CharSequence) value));
return bloom.findHash(hashValue);
case BINARY:
case FIXED:
hashValue = bloom.hash(Binary.fromConstantByteBuffer((ByteBuffer) value));
return bloom.findHash(hashValue);
case DECIMAL:
DecimalMetadata metadata = primitiveType.getDecimalMetadata();
int scale = metadata.getScale();
int precision = metadata.getPrecision();
byte[] requiredBytes = new byte[TypeUtil.decimalRequiredBytes(precision)];
byte[] binary = DecimalUtil.toReusedFixLengthBytes(precision, scale, (BigDecimal) value, requiredBytes);
hashValue = bloom.hash(Binary.fromConstantByteArray(binary));
return bloom.findHash(hashValue);
case UUID:
hashValue = bloom.hash(Binary.fromConstantByteArray(UUIDUtil.convert((UUID) value)));
return bloom.findHash(hashValue);
default:
return ROWS_MIGHT_MATCH;
}
default:
return ROWS_MIGHT_MATCH;
}
}
}
}
Original file line number Diff line number Diff line change
Expand Up @@ -344,6 +344,10 @@ public static boolean hasNonDictionaryPages(ColumnChunkMetaData meta) {
}
}

public static boolean hasNoBloomFilterPages(ColumnChunkMetaData meta) {
return meta.getBloomFilterOffset() == -1;
}

public static Dictionary readDictionary(ColumnDescriptor desc, PageReader pageSource) {
DictionaryPage dictionaryPage = pageSource.readDictionaryPage();
if (dictionaryPage != null) {
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Original file line number Diff line number Diff line change
Expand Up @@ -95,9 +95,11 @@ class ReadConf<T> {

ParquetMetricsRowGroupFilter statsFilter = null;
ParquetDictionaryRowGroupFilter dictFilter = null;
ParquetBloomRowGroupFilter bloomFilter = null;
if (filter != null) {
statsFilter = new ParquetMetricsRowGroupFilter(expectedSchema, filter, caseSensitive);
dictFilter = new ParquetDictionaryRowGroupFilter(expectedSchema, filter, caseSensitive);
bloomFilter = new ParquetBloomRowGroupFilter(expectedSchema, filter, caseSensitive);
}

long computedTotalValues = 0L;
Expand All @@ -106,7 +108,8 @@ class ReadConf<T> {
startRowPositions[i] = offsetToStartPos == null ? 0 : offsetToStartPos.get(rowGroup.getStartingPos());
boolean shouldRead = filter == null || (
statsFilter.shouldRead(typeWithIds, rowGroup) &&
dictFilter.shouldRead(typeWithIds, rowGroup, reader.getDictionaryReader(rowGroup)));
dictFilter.shouldRead(typeWithIds, rowGroup, reader.getDictionaryReader(rowGroup)) &&
bloomFilter.shouldRead(typeWithIds, rowGroup, reader.getBloomFilterDataReader(rowGroup)));
this.shouldSkip[i] = !shouldRead;
if (shouldRead) {
computedTotalValues += rowGroup.getRowCount();
Expand Down