aokolnychyi commented on a change in pull request #3400:
URL: https://github.com/apache/iceberg/pull/3400#discussion_r740534412
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatchQueryScan.java
##########
@@ -104,30 +144,100 @@
}
}
- if (splitSize != null) {
- scan = scan.option(TableProperties.SPLIT_SIZE, splitSize.toString());
+ for (Expression filter : filterExpressions()) {
+ scan = scan.filter(filter);
}
- if (splitLookback != null) {
- scan = scan.option(TableProperties.SPLIT_LOOKBACK,
splitLookback.toString());
+ try (CloseableIterable<FileScanTask> filesIterable = scan.planFiles()) {
+ this.files = Lists.newArrayList(filesIterable);
+ } catch (IOException e) {
+ throw new UncheckedIOException("Failed to close table scan: " + scan,
e);
}
+ }
- if (splitOpenFileCost != null) {
- scan = scan.option(TableProperties.SPLIT_OPEN_FILE_COST,
splitOpenFileCost.toString());
- }
+ return files;
+ }
- for (Expression filter : filterExpressions()) {
- scan = scan.filter(filter);
+ @Override
+ protected List<CombinedScanTask> tasks() {
+ if (tasks == null) {
+ CloseableIterable<FileScanTask> splitFiles = TableScanUtil.splitFiles(
+ CloseableIterable.withNoopClose(files()),
+ splitSize);
+ CloseableIterable<CombinedScanTask> scanTasks = TableScanUtil.planTasks(
+ splitFiles, splitSize,
+ splitLookback, splitOpenFileCost);
+ tasks = Lists.newArrayList(scanTasks);
+ }
+
+ return tasks;
+ }
+
+ @Override
+ public NamedReference[] filterAttributes() {
+ Set<Integer> partitionFieldSourceIds = Sets.newHashSet();
+
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ for (PartitionField field : spec.fields()) {
+ partitionFieldSourceIds.add(field.sourceId());
}
+ }
- try (CloseableIterable<CombinedScanTask> tasksIterable =
scan.planTasks()) {
- this.tasks = Lists.newArrayList(tasksIterable);
- } catch (IOException e) {
- throw new RuntimeIOException(e, "Failed to close table scan: %s",
scan);
+ Map<Integer, String> nameById =
TypeUtil.indexQuotedNameById(table().schema().asStruct());
Review comment:
Yeah, @rdblue is right. I'll add a test for the rename to be safe.
##########
File path: core/src/main/java/org/apache/iceberg/BaseMetadataTable.java
##########
@@ -34,7 +34,7 @@
* using a {@link StaticTableOperations}. This way no Catalog related calls
are needed when reading the table data after
* deserialization.
*/
-abstract class BaseMetadataTable implements Table, HasTableOperations,
Serializable {
+public abstract class BaseMetadataTable implements Table, HasTableOperations,
Serializable {
Review comment:
Reverting this change to use `TableScan` instead.
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/SparkConfParser.java
##########
@@ -34,7 +35,8 @@
private final Map<String, String> options;
SparkConfParser(SparkSession spark, Table table, Map<String, String>
options) {
- this.properties = table.properties();
+ // use table ops as metadata tables have empty properties
+ this.properties = ((HasTableOperations)
table).operations().current().properties();
Review comment:
Switching back to empty props for now.
##########
File path: api/src/main/java/org/apache/iceberg/types/IndexByName.java
##########
@@ -166,9 +177,10 @@ public void afterMapValue(Types.NestedField valueField) {
}
private void addField(String name, int fieldId) {
- String fullName = name;
+ String fullName = quote(name);
if (!fieldNames.isEmpty()) {
- fullName = DOT.join(DOT.join(fieldNames.descendingIterator()), name);
+ Iterator<String> quotedFieldNames =
Iterators.transform(fieldNames.descendingIterator(), this::quote);
+ fullName = DOT.join(DOT.join(quotedFieldNames), quote(name));
Review comment:
Added a variable.
##########
File path:
spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/source/TestRuntimeFiltering.java
##########
@@ -0,0 +1,300 @@
+/*
+ * 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.spark.source;
+
+import java.io.IOException;
+import java.io.UncheckedIOException;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileIO;
+import org.apache.iceberg.relocated.com.google.common.collect.Sets;
+import org.apache.iceberg.spark.SparkCatalogTestBase;
+import org.apache.iceberg.spark.SparkWriteOptions;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.analysis.NoSuchTableException;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Test;
+
+import static org.apache.spark.sql.functions.date_add;
+import static org.apache.spark.sql.functions.expr;
+
+public class TestRuntimeFiltering extends SparkCatalogTestBase {
+
+ public TestRuntimeFiltering(String catalogName, String implementation,
Map<String, String> config) {
+ super(catalogName, implementation, config);
+ }
+
+ @After
+ public void removeTables() {
+ sql("DROP TABLE IF EXISTS %s", tableName);
+ sql("DROP TABLE IF EXISTS dim");
+ }
+
+ @Test
+ public void testIdentityPartitionedTable() throws NoSuchTableException {
+ sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " +
+ "USING iceberg " +
+ "PARTITIONED BY (date)", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 10)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ String query = String.format(
+ "SELECT f.* FROM %s f JOIN dim d ON f.date = d.date AND d.id = 1 ORDER
BY id",
+ tableName);
+
+ assertQueryContainsRuntimeFilter(query);
+
+ deleteNotMatchingFiles(Expressions.equal("date", 1), 3);
Review comment:
Yeah, correct.
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatchQueryScan.java
##########
@@ -46,7 +69,11 @@
private final Long splitSize;
private final Integer splitLookback;
private final Long splitOpenFileCost;
+ private final List<Expression> runtimeFilterExpressions;
+ private TableScan scan = null; // lazy scan
Review comment:
@rdblue, I've added a scan but I still build it in this class to reduce
the amount of changes in this PR.
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatchQueryScan.java
##########
@@ -74,60 +101,158 @@
throw new IllegalArgumentException("Cannot only specify option
end-snapshot-id to do incremental scan");
}
- // look for split behavior overrides in options
- this.splitSize = Spark3Util.propertyAsLong(options,
SparkReadOptions.SPLIT_SIZE, null);
- this.splitLookback = Spark3Util.propertyAsInt(options,
SparkReadOptions.LOOKBACK, null);
- this.splitOpenFileCost = Spark3Util.propertyAsLong(options,
SparkReadOptions.FILE_OPEN_COST, null);
+ this.splitSize = table instanceof BaseMetadataTable ?
readConf.metadataSplitSize() : readConf.splitSize();
+ this.splitLookback = readConf.splitLookback();
+ this.splitOpenFileCost = readConf.splitOpenFileCost();
+ this.runtimeFilterExpressions = Lists.newArrayList();
+ }
+
+ private Set<Integer> specIds() {
+ if (specIds == null) {
+ Set<Integer> specIdSet = Sets.newHashSet();
+ for (FileScanTask file : files()) {
+ specIdSet.add(file.spec().specId());
+ }
+ this.specIds = specIdSet;
+ }
+
+ return specIds;
+ }
+
+ private List<FileScanTask> files() {
+ if (files == null) {
+ this.files = planFiles();
+ }
+
+ return files;
+ }
+
+ private List<FileScanTask> planFiles() {
+ TableScan scan = table()
+ .newScan()
+ .option(TableProperties.SPLIT_SIZE, String.valueOf(splitSize))
+ .option(TableProperties.SPLIT_LOOKBACK, String.valueOf(splitLookback))
+ .option(TableProperties.SPLIT_OPEN_FILE_COST,
String.valueOf(splitOpenFileCost))
+ .caseSensitive(caseSensitive())
+ .project(expectedSchema());
+
+ if (snapshotId != null) {
+ scan = scan.useSnapshot(snapshotId);
+ }
+
+ if (asOfTimestamp != null) {
+ scan = scan.asOfTime(asOfTimestamp);
+ }
+
+ if (startSnapshotId != null) {
+ if (endSnapshotId != null) {
+ scan = scan.appendsBetween(startSnapshotId, endSnapshotId);
+ } else {
+ scan = scan.appendsAfter(startSnapshotId);
+ }
+ }
+
+ for (Expression filter : filterExpressions()) {
+ scan = scan.filter(filter);
+ }
+
+ try (CloseableIterable<FileScanTask> filesIterable = scan.planFiles()) {
+ return Lists.newArrayList(filesIterable);
+ } catch (IOException e) {
+ throw new UncheckedIOException("Failed to close table scan: " + scan, e);
+ }
}
@Override
protected List<CombinedScanTask> tasks() {
if (tasks == null) {
- TableScan scan = table()
- .newScan()
- .caseSensitive(caseSensitive())
- .project(expectedSchema());
+ CloseableIterable<FileScanTask> splitFiles = TableScanUtil.splitFiles(
+ CloseableIterable.withNoopClose(files()),
+ splitSize);
+ CloseableIterable<CombinedScanTask> scanTasks = TableScanUtil.planTasks(
+ splitFiles, splitSize,
+ splitLookback, splitOpenFileCost);
+ tasks = Lists.newArrayList(scanTasks);
+ }
- if (snapshotId != null) {
- scan = scan.useSnapshot(snapshotId);
- }
+ return tasks;
+ }
- if (asOfTimestamp != null) {
- scan = scan.asOfTime(asOfTimestamp);
- }
+ @Override
+ public NamedReference[] filterAttributes() {
+ Set<Integer> partitionFieldSourceIds = Sets.newHashSet();
- if (startSnapshotId != null) {
- if (endSnapshotId != null) {
- scan = scan.appendsBetween(startSnapshotId, endSnapshotId);
- } else {
- scan = scan.appendsAfter(startSnapshotId);
- }
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ for (PartitionField field : spec.fields()) {
+ partitionFieldSourceIds.add(field.sourceId());
}
+ }
- if (splitSize != null) {
- scan = scan.option(TableProperties.SPLIT_SIZE, splitSize.toString());
- }
+ Map<Integer, String> quotedNameById = TypeUtil.indexQuotedNameById(
+ expectedSchema().asStruct(),
+ name -> String.format("`%s`", name.replace("`", "``")));
- if (splitLookback != null) {
- scan = scan.option(TableProperties.SPLIT_LOOKBACK,
splitLookback.toString());
- }
+ return partitionFieldSourceIds.stream()
+ .filter(fieldId -> expectedSchema().findField(fieldId) != null)
+ .map(fieldId ->
Spark3Util.toNamedReference(quotedNameById.get(fieldId)))
+ .toArray(NamedReference[]::new);
+ }
- if (splitOpenFileCost != null) {
- scan = scan.option(TableProperties.SPLIT_OPEN_FILE_COST,
splitOpenFileCost.toString());
+ @Override
+ public void filter(Filter[] filters) {
+ Expression runtimeFilterExpr = convertRuntimeFilters(filters);
+
+ if (runtimeFilterExpr != Expressions.alwaysTrue()) {
+ Map<Integer, Evaluator> evaluatorsBySpecId = Maps.newHashMap();
+
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ Expression inclusiveExpr =
Projections.inclusive(spec).project(runtimeFilterExpr);
+ Evaluator inclusive = new Evaluator(spec.partitionType(),
inclusiveExpr);
+ evaluatorsBySpecId.put(specId, inclusive);
}
- for (Expression filter : filterExpressions()) {
- scan = scan.filter(filter);
+ LOG.info("Trying to filter {} files using runtime filter {}",
files().size(), runtimeFilterExpr);
+
+ List<FileScanTask> filteredFiles = files().stream()
+ .filter(file -> {
+ Evaluator evaluator = evaluatorsBySpecId.get(file.spec().specId());
+ return evaluator.eval(file.file().partition());
+ })
+ .collect(Collectors.toList());
+
+ LOG.info("{}/{} files matched runtime filter {}", filteredFiles.size(),
files().size(), runtimeFilterExpr);
Review comment:
Maybe, @RussellSpitzer can cover that in his work on SQL metrics?
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatchQueryScan.java
##########
@@ -74,60 +101,158 @@
throw new IllegalArgumentException("Cannot only specify option
end-snapshot-id to do incremental scan");
}
- // look for split behavior overrides in options
- this.splitSize = Spark3Util.propertyAsLong(options,
SparkReadOptions.SPLIT_SIZE, null);
- this.splitLookback = Spark3Util.propertyAsInt(options,
SparkReadOptions.LOOKBACK, null);
- this.splitOpenFileCost = Spark3Util.propertyAsLong(options,
SparkReadOptions.FILE_OPEN_COST, null);
+ this.splitSize = table instanceof BaseMetadataTable ?
readConf.metadataSplitSize() : readConf.splitSize();
+ this.splitLookback = readConf.splitLookback();
+ this.splitOpenFileCost = readConf.splitOpenFileCost();
+ this.runtimeFilterExpressions = Lists.newArrayList();
+ }
+
+ private Set<Integer> specIds() {
+ if (specIds == null) {
+ Set<Integer> specIdSet = Sets.newHashSet();
+ for (FileScanTask file : files()) {
+ specIdSet.add(file.spec().specId());
+ }
+ this.specIds = specIdSet;
+ }
+
+ return specIds;
+ }
+
+ private List<FileScanTask> files() {
+ if (files == null) {
+ this.files = planFiles();
+ }
+
+ return files;
+ }
+
+ private List<FileScanTask> planFiles() {
+ TableScan scan = table()
+ .newScan()
+ .option(TableProperties.SPLIT_SIZE, String.valueOf(splitSize))
+ .option(TableProperties.SPLIT_LOOKBACK, String.valueOf(splitLookback))
+ .option(TableProperties.SPLIT_OPEN_FILE_COST,
String.valueOf(splitOpenFileCost))
+ .caseSensitive(caseSensitive())
+ .project(expectedSchema());
+
+ if (snapshotId != null) {
+ scan = scan.useSnapshot(snapshotId);
+ }
+
+ if (asOfTimestamp != null) {
+ scan = scan.asOfTime(asOfTimestamp);
+ }
+
+ if (startSnapshotId != null) {
+ if (endSnapshotId != null) {
+ scan = scan.appendsBetween(startSnapshotId, endSnapshotId);
+ } else {
+ scan = scan.appendsAfter(startSnapshotId);
+ }
+ }
+
+ for (Expression filter : filterExpressions()) {
+ scan = scan.filter(filter);
+ }
+
+ try (CloseableIterable<FileScanTask> filesIterable = scan.planFiles()) {
+ return Lists.newArrayList(filesIterable);
+ } catch (IOException e) {
+ throw new UncheckedIOException("Failed to close table scan: " + scan, e);
+ }
}
@Override
protected List<CombinedScanTask> tasks() {
if (tasks == null) {
- TableScan scan = table()
- .newScan()
- .caseSensitive(caseSensitive())
- .project(expectedSchema());
+ CloseableIterable<FileScanTask> splitFiles = TableScanUtil.splitFiles(
+ CloseableIterable.withNoopClose(files()),
+ splitSize);
+ CloseableIterable<CombinedScanTask> scanTasks = TableScanUtil.planTasks(
+ splitFiles, splitSize,
+ splitLookback, splitOpenFileCost);
+ tasks = Lists.newArrayList(scanTasks);
+ }
- if (snapshotId != null) {
- scan = scan.useSnapshot(snapshotId);
- }
+ return tasks;
+ }
- if (asOfTimestamp != null) {
- scan = scan.asOfTime(asOfTimestamp);
- }
+ @Override
+ public NamedReference[] filterAttributes() {
+ Set<Integer> partitionFieldSourceIds = Sets.newHashSet();
- if (startSnapshotId != null) {
- if (endSnapshotId != null) {
- scan = scan.appendsBetween(startSnapshotId, endSnapshotId);
- } else {
- scan = scan.appendsAfter(startSnapshotId);
- }
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ for (PartitionField field : spec.fields()) {
+ partitionFieldSourceIds.add(field.sourceId());
}
+ }
- if (splitSize != null) {
- scan = scan.option(TableProperties.SPLIT_SIZE, splitSize.toString());
- }
+ Map<Integer, String> quotedNameById = TypeUtil.indexQuotedNameById(
+ expectedSchema().asStruct(),
+ name -> String.format("`%s`", name.replace("`", "``")));
- if (splitLookback != null) {
- scan = scan.option(TableProperties.SPLIT_LOOKBACK,
splitLookback.toString());
- }
+ return partitionFieldSourceIds.stream()
+ .filter(fieldId -> expectedSchema().findField(fieldId) != null)
+ .map(fieldId ->
Spark3Util.toNamedReference(quotedNameById.get(fieldId)))
+ .toArray(NamedReference[]::new);
+ }
- if (splitOpenFileCost != null) {
- scan = scan.option(TableProperties.SPLIT_OPEN_FILE_COST,
splitOpenFileCost.toString());
+ @Override
+ public void filter(Filter[] filters) {
+ Expression runtimeFilterExpr = convertRuntimeFilters(filters);
+
+ if (runtimeFilterExpr != Expressions.alwaysTrue()) {
+ Map<Integer, Evaluator> evaluatorsBySpecId = Maps.newHashMap();
+
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ Expression inclusiveExpr =
Projections.inclusive(spec).project(runtimeFilterExpr);
+ Evaluator inclusive = new Evaluator(spec.partitionType(),
inclusiveExpr);
+ evaluatorsBySpecId.put(specId, inclusive);
}
- for (Expression filter : filterExpressions()) {
- scan = scan.filter(filter);
+ LOG.info("Trying to filter {} files using runtime filter {}",
files().size(), runtimeFilterExpr);
+
+ List<FileScanTask> filteredFiles = files().stream()
+ .filter(file -> {
+ Evaluator evaluator = evaluatorsBySpecId.get(file.spec().specId());
+ return evaluator.eval(file.file().partition());
+ })
+ .collect(Collectors.toList());
+
+ LOG.info("{}/{} files matched runtime filter {}", filteredFiles.size(),
files().size(), runtimeFilterExpr);
+
+ // don't invalidate tasks if the runtime filter had no effect to avoid
planning splits again
+ if (filteredFiles.size() < files().size()) {
+ this.specIds = null;
+ this.files = filteredFiles;
+ this.tasks = null;
}
- try (CloseableIterable<CombinedScanTask> tasksIterable =
scan.planTasks()) {
- this.tasks = Lists.newArrayList(tasksIterable);
- } catch (IOException e) {
- throw new RuntimeIOException(e, "Failed to close table scan: %s",
scan);
+ runtimeFilterExpressions.add(runtimeFilterExpr);
Review comment:
I added a comment.
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatchQueryScan.java
##########
@@ -74,60 +101,158 @@
throw new IllegalArgumentException("Cannot only specify option
end-snapshot-id to do incremental scan");
}
- // look for split behavior overrides in options
- this.splitSize = Spark3Util.propertyAsLong(options,
SparkReadOptions.SPLIT_SIZE, null);
- this.splitLookback = Spark3Util.propertyAsInt(options,
SparkReadOptions.LOOKBACK, null);
- this.splitOpenFileCost = Spark3Util.propertyAsLong(options,
SparkReadOptions.FILE_OPEN_COST, null);
+ this.splitSize = table instanceof BaseMetadataTable ?
readConf.metadataSplitSize() : readConf.splitSize();
+ this.splitLookback = readConf.splitLookback();
+ this.splitOpenFileCost = readConf.splitOpenFileCost();
+ this.runtimeFilterExpressions = Lists.newArrayList();
+ }
+
+ private Set<Integer> specIds() {
+ if (specIds == null) {
+ Set<Integer> specIdSet = Sets.newHashSet();
+ for (FileScanTask file : files()) {
+ specIdSet.add(file.spec().specId());
+ }
+ this.specIds = specIdSet;
+ }
+
+ return specIds;
+ }
+
+ private List<FileScanTask> files() {
+ if (files == null) {
+ this.files = planFiles();
+ }
+
+ return files;
+ }
+
+ private List<FileScanTask> planFiles() {
+ TableScan scan = table()
+ .newScan()
+ .option(TableProperties.SPLIT_SIZE, String.valueOf(splitSize))
+ .option(TableProperties.SPLIT_LOOKBACK, String.valueOf(splitLookback))
+ .option(TableProperties.SPLIT_OPEN_FILE_COST,
String.valueOf(splitOpenFileCost))
+ .caseSensitive(caseSensitive())
+ .project(expectedSchema());
+
+ if (snapshotId != null) {
+ scan = scan.useSnapshot(snapshotId);
+ }
+
+ if (asOfTimestamp != null) {
+ scan = scan.asOfTime(asOfTimestamp);
+ }
+
+ if (startSnapshotId != null) {
+ if (endSnapshotId != null) {
+ scan = scan.appendsBetween(startSnapshotId, endSnapshotId);
+ } else {
+ scan = scan.appendsAfter(startSnapshotId);
+ }
+ }
+
+ for (Expression filter : filterExpressions()) {
+ scan = scan.filter(filter);
+ }
+
+ try (CloseableIterable<FileScanTask> filesIterable = scan.planFiles()) {
+ return Lists.newArrayList(filesIterable);
+ } catch (IOException e) {
+ throw new UncheckedIOException("Failed to close table scan: " + scan, e);
+ }
}
@Override
protected List<CombinedScanTask> tasks() {
if (tasks == null) {
- TableScan scan = table()
- .newScan()
- .caseSensitive(caseSensitive())
- .project(expectedSchema());
+ CloseableIterable<FileScanTask> splitFiles = TableScanUtil.splitFiles(
+ CloseableIterable.withNoopClose(files()),
+ splitSize);
+ CloseableIterable<CombinedScanTask> scanTasks = TableScanUtil.planTasks(
+ splitFiles, splitSize,
+ splitLookback, splitOpenFileCost);
+ tasks = Lists.newArrayList(scanTasks);
+ }
- if (snapshotId != null) {
- scan = scan.useSnapshot(snapshotId);
- }
+ return tasks;
+ }
- if (asOfTimestamp != null) {
- scan = scan.asOfTime(asOfTimestamp);
- }
+ @Override
+ public NamedReference[] filterAttributes() {
+ Set<Integer> partitionFieldSourceIds = Sets.newHashSet();
- if (startSnapshotId != null) {
- if (endSnapshotId != null) {
- scan = scan.appendsBetween(startSnapshotId, endSnapshotId);
- } else {
- scan = scan.appendsAfter(startSnapshotId);
- }
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ for (PartitionField field : spec.fields()) {
+ partitionFieldSourceIds.add(field.sourceId());
}
+ }
- if (splitSize != null) {
- scan = scan.option(TableProperties.SPLIT_SIZE, splitSize.toString());
- }
+ Map<Integer, String> quotedNameById = TypeUtil.indexQuotedNameById(
+ expectedSchema().asStruct(),
+ name -> String.format("`%s`", name.replace("`", "``")));
- if (splitLookback != null) {
- scan = scan.option(TableProperties.SPLIT_LOOKBACK,
splitLookback.toString());
- }
+ return partitionFieldSourceIds.stream()
+ .filter(fieldId -> expectedSchema().findField(fieldId) != null)
+ .map(fieldId ->
Spark3Util.toNamedReference(quotedNameById.get(fieldId)))
+ .toArray(NamedReference[]::new);
+ }
- if (splitOpenFileCost != null) {
- scan = scan.option(TableProperties.SPLIT_OPEN_FILE_COST,
splitOpenFileCost.toString());
+ @Override
+ public void filter(Filter[] filters) {
+ Expression runtimeFilterExpr = convertRuntimeFilters(filters);
+
+ if (runtimeFilterExpr != Expressions.alwaysTrue()) {
+ Map<Integer, Evaluator> evaluatorsBySpecId = Maps.newHashMap();
+
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ Expression inclusiveExpr =
Projections.inclusive(spec).project(runtimeFilterExpr);
+ Evaluator inclusive = new Evaluator(spec.partitionType(),
inclusiveExpr);
+ evaluatorsBySpecId.put(specId, inclusive);
}
- for (Expression filter : filterExpressions()) {
- scan = scan.filter(filter);
+ LOG.info("Trying to filter {} files using runtime filter {}",
files().size(), runtimeFilterExpr);
+
+ List<FileScanTask> filteredFiles = files().stream()
+ .filter(file -> {
+ Evaluator evaluator = evaluatorsBySpecId.get(file.spec().specId());
+ return evaluator.eval(file.file().partition());
+ })
+ .collect(Collectors.toList());
+
+ LOG.info("{}/{} files matched runtime filter {}", filteredFiles.size(),
files().size(), runtimeFilterExpr);
+
+ // don't invalidate tasks if the runtime filter had no effect to avoid
planning splits again
+ if (filteredFiles.size() < files().size()) {
+ this.specIds = null;
+ this.files = filteredFiles;
+ this.tasks = null;
}
- try (CloseableIterable<CombinedScanTask> tasksIterable =
scan.planTasks()) {
- this.tasks = Lists.newArrayList(tasksIterable);
- } catch (IOException e) {
- throw new RuntimeIOException(e, "Failed to close table scan: %s",
scan);
+ runtimeFilterExpressions.add(runtimeFilterExpr);
+ }
+ }
+
+ private Expression convertRuntimeFilters(Filter[] filters) {
Review comment:
Added a comment.
##########
File path:
spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/source/TestRuntimeFiltering.java
##########
@@ -0,0 +1,300 @@
+/*
+ * 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.spark.source;
+
+import java.io.IOException;
+import java.io.UncheckedIOException;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileIO;
+import org.apache.iceberg.relocated.com.google.common.collect.Sets;
+import org.apache.iceberg.spark.SparkCatalogTestBase;
+import org.apache.iceberg.spark.SparkWriteOptions;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.analysis.NoSuchTableException;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Test;
+
+import static org.apache.spark.sql.functions.date_add;
+import static org.apache.spark.sql.functions.expr;
+
+public class TestRuntimeFiltering extends SparkCatalogTestBase {
+
+ public TestRuntimeFiltering(String catalogName, String implementation,
Map<String, String> config) {
+ super(catalogName, implementation, config);
+ }
+
+ @After
+ public void removeTables() {
+ sql("DROP TABLE IF EXISTS %s", tableName);
+ sql("DROP TABLE IF EXISTS dim");
+ }
+
+ @Test
+ public void testIdentityPartitionedTable() throws NoSuchTableException {
+ sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " +
+ "USING iceberg " +
+ "PARTITIONED BY (date)", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 10)
Review comment:
They use slightly different naming strategy so that would require more
refactoring.
I'd probably keep it as is for now if nobody minds.
##########
File path:
spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/source/TestRuntimeFiltering.java
##########
@@ -0,0 +1,300 @@
+/*
+ * 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.spark.source;
+
+import java.io.IOException;
+import java.io.UncheckedIOException;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileIO;
+import org.apache.iceberg.relocated.com.google.common.collect.Sets;
+import org.apache.iceberg.spark.SparkCatalogTestBase;
+import org.apache.iceberg.spark.SparkWriteOptions;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.analysis.NoSuchTableException;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Test;
+
+import static org.apache.spark.sql.functions.date_add;
+import static org.apache.spark.sql.functions.expr;
+
+public class TestRuntimeFiltering extends SparkCatalogTestBase {
+
+ public TestRuntimeFiltering(String catalogName, String implementation,
Map<String, String> config) {
+ super(catalogName, implementation, config);
+ }
+
+ @After
+ public void removeTables() {
+ sql("DROP TABLE IF EXISTS %s", tableName);
+ sql("DROP TABLE IF EXISTS dim");
+ }
+
+ @Test
+ public void testIdentityPartitionedTable() throws NoSuchTableException {
+ sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " +
+ "USING iceberg " +
+ "PARTITIONED BY (date)", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 10)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ String query = String.format(
+ "SELECT f.* FROM %s f JOIN dim d ON f.date = d.date AND d.id = 1 ORDER
BY id",
Review comment:
I've focused on testing filtering logic in Iceberg. It is up to Spark to
decide whether to trigger dynamic filtering or not. That logic is fairly
complicated and cost-based, which means it is fragile and may change, which
will make the tests unstable. That's why I kept filtering scenarios simple from
the Spark point of view.
##########
File path:
spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/source/TestRuntimeFiltering.java
##########
@@ -0,0 +1,300 @@
+/*
+ * 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.spark.source;
+
+import java.io.IOException;
+import java.io.UncheckedIOException;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import org.apache.iceberg.FileScanTask;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.expressions.Expression;
+import org.apache.iceberg.expressions.Expressions;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.io.FileIO;
+import org.apache.iceberg.relocated.com.google.common.collect.Sets;
+import org.apache.iceberg.spark.SparkCatalogTestBase;
+import org.apache.iceberg.spark.SparkWriteOptions;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.catalyst.analysis.NoSuchTableException;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.Test;
+
+import static org.apache.spark.sql.functions.date_add;
+import static org.apache.spark.sql.functions.expr;
+
+public class TestRuntimeFiltering extends SparkCatalogTestBase {
+
+ public TestRuntimeFiltering(String catalogName, String implementation,
Map<String, String> config) {
+ super(catalogName, implementation, config);
+ }
+
+ @After
+ public void removeTables() {
+ sql("DROP TABLE IF EXISTS %s", tableName);
+ sql("DROP TABLE IF EXISTS dim");
+ }
+
+ @Test
+ public void testIdentityPartitionedTable() throws NoSuchTableException {
+ sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " +
+ "USING iceberg " +
+ "PARTITIONED BY (date)", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 10)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ String query = String.format(
+ "SELECT f.* FROM %s f JOIN dim d ON f.date = d.date AND d.id = 1 ORDER
BY id",
+ tableName);
+
+ assertQueryContainsRuntimeFilter(query);
+
+ deleteNotMatchingFiles(Expressions.equal("date", 1), 3);
+
+ assertEquals("Should have expected rows",
+ sql("SELECT * FROM %s WHERE date = DATE '1970-01-02' ORDER BY id",
tableName),
+ sql(query));
+ }
+
+ @Test
+ public void testBucketedTable() throws NoSuchTableException {
+ sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP) " +
+ "USING iceberg " +
+ "PARTITIONED BY (bucket(8, id))", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 2)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ String query = String.format(
+ "SELECT f.* FROM %s f JOIN dim d ON f.id = d.id AND d.date = DATE
'1970-01-02' ORDER BY date",
+ tableName);
+
+ assertQueryContainsRuntimeFilter(query);
+
+ deleteNotMatchingFiles(Expressions.equal("id", 1), 7);
+
+ assertEquals("Should have expected rows",
+ sql("SELECT * FROM %s WHERE id = 1 ORDER BY date", tableName),
+ sql(query));
+ }
+
+ @Test
+ public void testBucketedTableWithMultipleSpecs() throws NoSuchTableException
{
+ sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP)
USING iceberg", tableName);
+
+ Dataset<Row> df1 = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 2 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+ df1.coalesce(1).writeTo(tableName).append();
+
+ Table table = validationCatalog.loadTable(tableIdent);
+ table.updateSpec()
+ .addField(Expressions.bucket("id", 8))
+ .commit();
+
+ sql("REFRESH TABLE %s", tableName);
+
+ Dataset<Row> df2 = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+
df2.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 2)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ String query = String.format(
+ "SELECT f.* FROM %s f JOIN dim d ON f.id = d.id AND d.date = DATE
'1970-01-02' ORDER BY date",
+ tableName);
+
+ assertQueryContainsRuntimeFilter(query);
+
+ deleteNotMatchingFiles(Expressions.equal("id", 1), 7);
+
+ assertEquals("Should have expected rows",
+ sql("SELECT * FROM %s WHERE id = 1 ORDER BY date", tableName),
+ sql(query));
+ }
+
+ @Test
+ public void testSourceColumnWithDots() throws NoSuchTableException {
+ sql("CREATE TABLE %s (`i.d` BIGINT, data STRING, date DATE, ts TIMESTAMP)
" +
+ "USING iceberg " +
+ "PARTITIONED BY (bucket(8, `i.d`))", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumnRenamed("id", "i.d")
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"),
expr("CAST(`i.d` % 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("`i.d`", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("SELECT * FROM %s WHERE `i.d` = 1", tableName);
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 2)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ String query = String.format(
+ "SELECT f.* FROM %s f JOIN dim d ON f.`i.d` = d.id AND d.date = DATE
'1970-01-02' ORDER BY date",
+ tableName);
+
+ assertQueryContainsRuntimeFilter(query);
+
+ deleteNotMatchingFiles(Expressions.equal("i.d", 1), 7);
+
+ sql(query);
+
+ assertEquals("Should have expected rows",
+ sql("SELECT * FROM %s WHERE `i.d` = 1 ORDER BY date", tableName),
+ sql(query));
+ }
+
+ @Test
+ public void testSourceColumnWithBackticks() throws NoSuchTableException {
+ sql("CREATE TABLE %s (`i``d` BIGINT, data STRING, date DATE, ts TIMESTAMP)
" +
+ "USING iceberg " +
+ "PARTITIONED BY (bucket(8, `i``d`))", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumnRenamed("id", "i`d")
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"),
expr("CAST(`i``d` % 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("`i``d`", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).option(SparkWriteOptions.FANOUT_ENABLED,
"true").append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 2)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ String query = String.format(
+ "SELECT f.* FROM %s f JOIN dim d ON f.`i``d` = d.id AND d.date = DATE
'1970-01-02' ORDER BY date",
+ tableName);
+
+ assertQueryContainsRuntimeFilter(query);
+
+ deleteNotMatchingFiles(Expressions.equal("i`d", 1), 7);
+
+ assertEquals("Should have expected rows",
+ sql("SELECT * FROM %s WHERE `i``d` = 1 ORDER BY date", tableName),
+ sql(query));
+ }
+
+ @Test
+ public void testUnpartitionedTable() throws NoSuchTableException {
+ sql("CREATE TABLE %s (id BIGINT, data STRING, date DATE, ts TIMESTAMP)
USING iceberg", tableName);
+
+ Dataset<Row> df = spark.range(1, 100)
+ .withColumn("date", date_add(expr("DATE '1970-01-01'"), expr("CAST(id
% 4 AS INT)")))
+ .withColumn("ts", expr("TO_TIMESTAMP(date)"))
+ .withColumn("data", expr("CAST(date AS STRING)"))
+ .select("id", "data", "date", "ts");
+
+ df.coalesce(1).writeTo(tableName).append();
+
+ sql("CREATE TABLE dim (id BIGINT, date DATE) USING parquet");
+ Dataset<Row> dimDF = spark.range(1, 2)
+ .withColumn("date", expr("DATE '1970-01-02'"))
+ .select("id", "date");
+ dimDF.coalesce(1).write().mode("append").insertInto("dim");
+
+ assertEquals("Should have expected rows",
Review comment:
Added a check above.
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatchQueryScan.java
##########
@@ -74,17 +100,31 @@
throw new IllegalArgumentException("Cannot only specify option
end-snapshot-id to do incremental scan");
}
- // look for split behavior overrides in options
- this.splitSize = Spark3Util.propertyAsLong(options,
SparkReadOptions.SPLIT_SIZE, null);
- this.splitLookback = Spark3Util.propertyAsInt(options,
SparkReadOptions.LOOKBACK, null);
- this.splitOpenFileCost = Spark3Util.propertyAsLong(options,
SparkReadOptions.FILE_OPEN_COST, null);
+ this.splitSize = table instanceof BaseMetadataTable ?
readConf.metadataSplitSize() : readConf.splitSize();
Review comment:
Switched to `TableScan`.
##########
File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/source/SparkBatchQueryScan.java
##########
@@ -104,30 +144,100 @@
}
}
- if (splitSize != null) {
- scan = scan.option(TableProperties.SPLIT_SIZE, splitSize.toString());
+ for (Expression filter : filterExpressions()) {
+ scan = scan.filter(filter);
}
- if (splitLookback != null) {
- scan = scan.option(TableProperties.SPLIT_LOOKBACK,
splitLookback.toString());
+ try (CloseableIterable<FileScanTask> filesIterable = scan.planFiles()) {
+ this.files = Lists.newArrayList(filesIterable);
+ } catch (IOException e) {
+ throw new UncheckedIOException("Failed to close table scan: " + scan,
e);
}
+ }
- if (splitOpenFileCost != null) {
- scan = scan.option(TableProperties.SPLIT_OPEN_FILE_COST,
splitOpenFileCost.toString());
- }
+ return files;
+ }
- for (Expression filter : filterExpressions()) {
- scan = scan.filter(filter);
+ @Override
+ protected List<CombinedScanTask> tasks() {
+ if (tasks == null) {
+ CloseableIterable<FileScanTask> splitFiles = TableScanUtil.splitFiles(
+ CloseableIterable.withNoopClose(files()),
+ splitSize);
+ CloseableIterable<CombinedScanTask> scanTasks = TableScanUtil.planTasks(
+ splitFiles, splitSize,
+ splitLookback, splitOpenFileCost);
+ tasks = Lists.newArrayList(scanTasks);
+ }
+
+ return tasks;
+ }
+
+ @Override
+ public NamedReference[] filterAttributes() {
+ Set<Integer> partitionFieldSourceIds = Sets.newHashSet();
+
+ for (Integer specId : specIds()) {
+ PartitionSpec spec = table().specs().get(specId);
+ for (PartitionField field : spec.fields()) {
+ partitionFieldSourceIds.add(field.sourceId());
}
+ }
- try (CloseableIterable<CombinedScanTask> tasksIterable =
scan.planTasks()) {
- this.tasks = Lists.newArrayList(tasksIterable);
- } catch (IOException e) {
- throw new RuntimeIOException(e, "Failed to close table scan: %s",
scan);
+ Map<Integer, String> nameById =
TypeUtil.indexQuotedNameById(table().schema().asStruct());
Review comment:
Added a test when the source column is renamed.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
