org.apache.iceberg.spark.source.SparkTable Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of iceberg-spark3 Show documentation
A table format for huge analytic datasets
There is a newer version: 0.13.2
/*
 * 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.Map;
import java.util.Set;
import org.apache.iceberg.Table;
import org.apache.iceberg.TableProperties;
import org.apache.iceberg.exceptions.ValidationException;
import org.apache.iceberg.expressions.Expression;
import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap;
import org.apache.iceberg.relocated.com.google.common.collect.ImmutableSet;
import org.apache.iceberg.relocated.com.google.common.collect.Sets;
import org.apache.iceberg.spark.Spark3Util;
import org.apache.iceberg.spark.SparkFilters;
import org.apache.iceberg.spark.SparkSchemaUtil;
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.connector.catalog.SupportsDelete;
import org.apache.spark.sql.connector.catalog.SupportsRead;
import org.apache.spark.sql.connector.catalog.SupportsWrite;
import org.apache.spark.sql.connector.catalog.TableCapability;
import org.apache.spark.sql.connector.expressions.Transform;
import org.apache.spark.sql.connector.read.ScanBuilder;
import org.apache.spark.sql.connector.write.LogicalWriteInfo;
import org.apache.spark.sql.connector.write.WriteBuilder;
import org.apache.spark.sql.sources.Filter;
import org.apache.spark.sql.types.StructType;
import org.apache.spark.sql.util.CaseInsensitiveStringMap;

public class SparkTable implements org.apache.spark.sql.connector.catalog.Table,
    SupportsRead, SupportsWrite, SupportsDelete {

  private static final Set RESERVED_PROPERTIES = Sets.newHashSet("provider", "format", "current-snapshot-id");
  private static final Set CAPABILITIES = ImmutableSet.of(
      TableCapability.BATCH_READ,
      TableCapability.BATCH_WRITE,
      TableCapability.STREAMING_WRITE,
      TableCapability.OVERWRITE_BY_FILTER,
      TableCapability.OVERWRITE_DYNAMIC);

  private final Table icebergTable;
  private final StructType requestedSchema;
  private StructType lazyTableSchema = null;
  private SparkSession lazySpark = null;

  public SparkTable(Table icebergTable) {
    this(icebergTable, null);
  }

  public SparkTable(Table icebergTable, StructType requestedSchema) {
    this.icebergTable = icebergTable;
    this.requestedSchema = requestedSchema;

    if (requestedSchema != null) {
      // convert the requested schema to throw an exception if any requested fields are unknown
      SparkSchemaUtil.convert(icebergTable.schema(), requestedSchema);
    }
  }

  private SparkSession sparkSession() {
    if (lazySpark == null) {
      this.lazySpark = SparkSession.active();
    }

    return lazySpark;
  }

  public Table table() {
    return icebergTable;
  }

  @Override
  public String name() {
    return icebergTable.toString();
  }

  @Override
  public StructType schema() {
    if (lazyTableSchema == null) {
      if (requestedSchema != null) {
        this.lazyTableSchema = SparkSchemaUtil.convert(SparkSchemaUtil.prune(icebergTable.schema(), requestedSchema));
      } else {
        this.lazyTableSchema = SparkSchemaUtil.convert(icebergTable.schema());
      }
    }

    return lazyTableSchema;
  }

  @Override
  public Transform[] partitioning() {
    return Spark3Util.toTransforms(icebergTable.spec());
  }

  @Override
  public Map properties() {
    ImmutableMap.Builder propsBuilder = ImmutableMap.builder();

    String fileFormat = icebergTable.properties()
        .getOrDefault(TableProperties.DEFAULT_FILE_FORMAT, TableProperties.DEFAULT_FILE_FORMAT_DEFAULT);
    propsBuilder.put("format", "iceberg/" + fileFormat);
    propsBuilder.put("provider", "iceberg");
    String currentSnapshotId = icebergTable.currentSnapshot() != null ?
        String.valueOf(icebergTable.currentSnapshot().snapshotId()) : "none";
    propsBuilder.put("current-snapshot-id", currentSnapshotId);

    icebergTable.properties().entrySet().stream()
        .filter(entry -> !RESERVED_PROPERTIES.contains(entry.getKey()))
        .forEach(propsBuilder::put);

    return propsBuilder.build();
  }

  @Override
  public Set capabilities() {
    return CAPABILITIES;
  }

  @Override
  public ScanBuilder newScanBuilder(CaseInsensitiveStringMap options) {
    SparkScanBuilder scanBuilder = new SparkScanBuilder(sparkSession(), icebergTable, options);

    if (requestedSchema != null) {
      scanBuilder.pruneColumns(requestedSchema);
    }

    return scanBuilder;
  }

  @Override
  public WriteBuilder newWriteBuilder(LogicalWriteInfo info) {
    return new SparkWriteBuilder(sparkSession(), icebergTable, info);
  }

  @Override
  public void deleteWhere(Filter[] filters) {
    Expression deleteExpr = SparkFilters.convert(filters);

    try {
      icebergTable.newDelete()
          .set("spark.app.id", sparkSession().sparkContext().applicationId())
          .deleteFromRowFilter(deleteExpr)
          .commit();
    } catch (ValidationException e) {
      throw new IllegalArgumentException("Failed to cleanly delete data files matching: " + deleteExpr, e);
    }
  }

  @Override
  public String toString() {
    return icebergTable.toString();
  }
}