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A table format for huge analytic datasets
/*
* 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.util.Set;
import org.apache.iceberg.ChangelogUtil;
import org.apache.iceberg.MetadataColumns;
import org.apache.iceberg.Partitioning;
import org.apache.iceberg.Schema;
import org.apache.iceberg.relocated.com.google.common.collect.ImmutableSet;
import org.apache.iceberg.spark.SparkSchemaUtil;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.connector.catalog.MetadataColumn;
import org.apache.spark.sql.connector.catalog.SupportsMetadataColumns;
import org.apache.spark.sql.connector.catalog.SupportsRead;
import org.apache.spark.sql.connector.catalog.Table;
import org.apache.spark.sql.connector.catalog.TableCapability;
import org.apache.spark.sql.connector.read.Scan;
import org.apache.spark.sql.connector.read.ScanBuilder;
import org.apache.spark.sql.types.DataType;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.StructType;
import org.apache.spark.sql.util.CaseInsensitiveStringMap;
public class SparkChangelogTable implements Table, SupportsRead, SupportsMetadataColumns {
public static final String TABLE_NAME = "changes";
private static final Set CAPABILITIES =
ImmutableSet.of(TableCapability.BATCH_READ);
private final org.apache.iceberg.Table icebergTable;
private final boolean refreshEagerly;
private SparkSession lazySpark = null;
private StructType lazyTableSparkType = null;
private Schema lazyChangelogSchema = null;
public SparkChangelogTable(org.apache.iceberg.Table icebergTable, boolean refreshEagerly) {
this.icebergTable = icebergTable;
this.refreshEagerly = refreshEagerly;
}
@Override
public String name() {
return icebergTable.name() + "." + TABLE_NAME;
}
@Override
public StructType schema() {
if (lazyTableSparkType == null) {
this.lazyTableSparkType = SparkSchemaUtil.convert(changelogSchema());
}
return lazyTableSparkType;
}
@Override
public Set capabilities() {
return CAPABILITIES;
}
@Override
public ScanBuilder newScanBuilder(CaseInsensitiveStringMap options) {
if (refreshEagerly) {
icebergTable.refresh();
}
return new SparkScanBuilder(spark(), icebergTable, changelogSchema(), options) {
@Override
public Scan build() {
return buildChangelogScan();
}
};
}
private Schema changelogSchema() {
if (lazyChangelogSchema == null) {
this.lazyChangelogSchema = ChangelogUtil.changelogSchema(icebergTable.schema());
}
return lazyChangelogSchema;
}
private SparkSession spark() {
if (lazySpark == null) {
this.lazySpark = SparkSession.active();
}
return lazySpark;
}
@Override
public MetadataColumn[] metadataColumns() {
DataType sparkPartitionType = SparkSchemaUtil.convert(Partitioning.partitionType(icebergTable));
return new MetadataColumn[] {
new SparkMetadataColumn(MetadataColumns.SPEC_ID.name(), DataTypes.IntegerType, false),
new SparkMetadataColumn(MetadataColumns.PARTITION_COLUMN_NAME, sparkPartitionType, true),
new SparkMetadataColumn(MetadataColumns.FILE_PATH.name(), DataTypes.StringType, false),
new SparkMetadataColumn(MetadataColumns.ROW_POSITION.name(), DataTypes.LongType, false),
new SparkMetadataColumn(MetadataColumns.IS_DELETED.name(), DataTypes.BooleanType, false)
};
}
}