content: /*
   * 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.beam.runners.spark;
  
  import org.apache.beam.runners.spark.structuredstreaming.SparkStructuredStreamingRunner;
  import org.apache.beam.sdk.annotations.Internal;
  import org.apache.beam.sdk.options.ApplicationNameOptions;
  import org.apache.beam.sdk.options.Default;
  import org.apache.beam.sdk.options.DefaultValueFactory;
  import org.apache.beam.sdk.options.Description;
  import org.apache.beam.sdk.options.FileStagingOptions;
  import org.apache.beam.sdk.options.PipelineOptions;
  import org.apache.beam.sdk.options.StreamingOptions;
  import org.apache.beam.sdk.util.construction.resources.PipelineResources;
  
  /**
   * Spark runner {@link PipelineOptions} handles Spark execution-related configurations, such as the
   * master address, and other user-related knobs.
   */
  public interface SparkCommonPipelineOptions
      extends PipelineOptions, StreamingOptions, ApplicationNameOptions, FileStagingOptions {
  
    String DEFAULT_MASTER_URL = "local[4]";
  
    @Description("The url of the spark master to connect to, (e.g. spark://host:port, local[4]).")
    @Default.String(DEFAULT_MASTER_URL)
    String getSparkMaster();
  
    void setSparkMaster(String master);
  
    @Description(
        "A checkpoint directory for streaming resilience, ignored in batch. "
            + "For durability, a reliable filesystem such as HDFS/S3/GS is necessary.")
    @Default.InstanceFactory(TmpCheckpointDirFactory.class)
    String getCheckpointDir();
  
    void setCheckpointDir(String checkpointDir);
  
    @Description("Batch default storage level")
    @Default.InstanceFactory(StorageLevelFactory.class)
    String getStorageLevel();
  
    void setStorageLevel(String storageLevel);
  
    @Description("Enable/disable sending aggregator values to Spark's metric sinks")
    @Default.Boolean(true)
    Boolean getEnableSparkMetricSinks();
  
    void setEnableSparkMetricSinks(Boolean enableSparkMetricSinks);
  
    @Description(
        "When set to true, runner will try to prefer GroupByKey translation which can handle huge values and "
            + "does not require them to fit into memory. This will most likely have performance impact "
            + "for pipelines which does not work with huge values, hence it is disabled by default.")
    @Default.Boolean(false)
    Boolean getPreferGroupByKeyToHandleHugeValues();
  
    void setPreferGroupByKeyToHandleHugeValues(Boolean preferGroupByKeyToHandleHugeValues);
  
    /**
     * Returns the default checkpoint directory of /tmp/${job.name}. For testing purposes only.
     * Production applications should use a reliable filesystem such as HDFS/S3/GS.
     */
    class TmpCheckpointDirFactory implements DefaultValueFactory<String> {
      @Override
      public String create(PipelineOptions options) {
        return "/tmp/" + options.getJobName();
      }
    }
  
    /**
     * Classpath contains non jar files (eg. directories with .class files or empty directories) will
     * cause exception in running log. Though the {@link org.apache.spark.SparkContext} can handle
     * this when running in local master, it's better not to include non-jars files in classpath.
     */
    @Internal
    static void prepareFilesToStage(SparkCommonPipelineOptions options) {
      if (!options.getSparkMaster().matches("local\\[?\\d*]?")) {
        PipelineResources.prepareFilesForStaging(options);
      }
    }
  
    /**
     * Returns Spark's default storage level for the Dataset or RDD API based on the respective
     * runner.
     */
    class StorageLevelFactory implements DefaultValueFactory<String> {
      @Override
      public String create(PipelineOptions options) {
        return SparkStructuredStreamingRunner.class.equals(options.getRunner())
            ? "MEMORY_AND_DISK"
            : "MEMORY_ONLY";
      }
    }
  }
  