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 com.datastax.spark.connector.japi.rdd;
  
  import java.util.Collection;
  
  import scala.Tuple2;
  import scala.collection.Seq;
  import scala.reflect.ClassTag;
  
  import static com.datastax.spark.connector.japi.CassandraJavaUtil.toSelectableColumnRefs;
  import static com.datastax.spark.connector.util.JavaApiHelper.getClassTag;
  import static com.datastax.spark.connector.util.JavaApiHelper.toScalaSeq;
  import org.apache.spark.api.java.JavaPairRDD;
  import org.apache.spark.api.java.function.Function;
  
  import com.datastax.spark.connector.ColumnRef;
  import com.datastax.spark.connector.cql.CassandraConnector;
  import com.datastax.spark.connector.japi.PairRDDJavaFunctions;
  import com.datastax.spark.connector.rdd.CassandraRDD;
  import com.datastax.spark.connector.rdd.ReadConf;
  import com.datastax.spark.connector.util.JavaApiHelper;
  
  @SuppressWarnings("UnusedDeclaration")
  public class CassandraJavaPairRDD<K, V> extends JavaPairRDD<K, V> {
  
      public CassandraJavaPairRDD(
              CassandraRDD<Tuple2<K, V>> rdd,
              ClassTag<K> keyClassTag,
              ClassTag<V> valueClassTag
      ) {
          super(rdd, keyClassTag, valueClassTag);
      }
  
      public CassandraJavaPairRDD(
              CassandraRDD<Tuple2<K, V>> rdd,
              Class<K> keyClass,
              Class<V> valueClass
      ) {
          super(rdd, getClassTag(keyClass), getClassTag(valueClass));
      }
  
      private CassandraJavaPairRDD<K, V> wrap(CassandraRDD<Tuple2<K, V>> newRDD) {
          return new CassandraJavaPairRDD<>(newRDD, kClassTag(), vClassTag());
      }
  
      @Override
      public CassandraRDD<Tuple2<K, V>> rdd() {
          return (CassandraRDD<Tuple2<K, V>>) super.rdd();
      }
  
      /**
       * Narrows down the selected set of columns.
       * <p/>
       * Use this for better performance, when you don't need all the columns in the result RDD. When
       * called multiple times, it selects the subset of the already selected columns, so after a column
       * was removed by the previous {@code select} call, it is not possible to add it back.
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> select(String... columnNames) {
          Seq<ColumnRef> columnRefs = toScalaSeq(toSelectableColumnRefs(columnNames));
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().select(columnRefs.toSeq());
          return wrap(newRDD);
      }
  
      /**
       * Narrows down the selected set of columns.
       * <p/>
       * Use this for better performance, when you don't need all the columns in the result RDD. When
       * called multiple times, it selects the subset of the already selected columns, so after a column
       * was removed by the previous {@code select} call, it is not possible to add it back.
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> select(ColumnRef... selectionColumns) {
          Seq<ColumnRef> columnRefs = JavaApiHelper.toScalaSeq(selectionColumns);
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().select(columnRefs.toSeq());
          return wrap(newRDD);
      }
  
      /**
       * Adds a CQL {@code WHERE} predicate(s) to the query.
       * <p/>
       * Useful for leveraging secondary indexes in Cassandra. Implicitly adds an {@code ALLOW FILTERING}
       * clause to the {@code WHERE} clause, however beware that some predicates might be rejected by
       * Cassandra, particularly in cases when they filter on an unindexed, non-clustering column.
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> where(String cqlWhereClause, Object... args) {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().where(cqlWhereClause, toScalaSeq(args));
          return wrap(newRDD);
      }
  
      /**
       * Forces the rows within a selected Cassandra partition to be returned in ascending order (if
       * possible).
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> withAscOrder() {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().withAscOrder();
          return wrap(newRDD);
      }
  
      /**
       * Forces the rows within a selected Cassandra partition to be returned in descending order (if
       * possible).
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> withDescOrder() {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().withDescOrder();
          return wrap(newRDD);
      }
  
      /**
       * Adds the limit clause to CQL select statement. The limit will be applied for each created Spark
       * partition. In other words, unless the data are fetched from a single Cassandra partition the
       * number of results is unpredictable.
       * <p/>
       * The main purpose of passing limit clause is to fetch top n rows from a single Cassandra partition
       * when the table is designed so that it uses clustering keys and a partition key predicate is passed
       * to the where clause.
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> limit(Long rowsNumber) {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().limit(rowsNumber);
          return wrap(newRDD);
      }
  
      /**
       * Adds the PER PARTITION LIMIT clause to CQL select statement. The limit will be applied for each
       * Cassandra Partition
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> perPartitionLimit(Long rowsNumber) {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().perPartitionLimit(rowsNumber);
          return wrap(newRDD);
      }
  
      /**
       * Returns the names of columns to be selected from the table.
       */
      @SuppressWarnings("RedundantCast")
      public ColumnRef[] selectedColumnRefs() {
          ClassTag<ColumnRef> classTag = getClassTag(ColumnRef.class);
          return (ColumnRef[]) rdd().selectedColumnRefs().toArray(classTag);
      }
  
      /**
       * Returns the names of columns to be selected from the table.
       */
      @SuppressWarnings("RedundantCast")
      public String[] selectedColumnNames() {
          ClassTag<String> classTag = getClassTag(String.class);
          return (String[]) rdd().selectedColumnNames().toArray(classTag);
      }
  
      /**
       * Returns a copy of this RDD with connector changed to the specified one.
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> withConnector(CassandraConnector connector) {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().withConnector(connector);
          return wrap(newRDD);
      }
  
      /**
       * Returns a copy of this RDD with read configuration changed to the specified one.
       */
      @SuppressWarnings("unchecked")
      public CassandraJavaPairRDD<K, V> withReadConf(ReadConf config) {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().withReadConf(config);
          return wrap(newRDD);
      }
  
      /**
       * Produces the empty CassandraRDD which has the same signature and properties, but it does not
       * perform any validation and it does not even try to return any rows.
       */
      public CassandraJavaPairRDD<K, V> toEmptyCassandraRDD() {
          CassandraRDD<Tuple2<K, V>> newRDD = rdd().toEmptyCassandraRDD();
          return wrap(newRDD);
      }
  
      /**
       * Groups items with the same key, assuming the items with the same key are next to each other in the
       * collection. It does not perform shuffle, therefore it is much faster than using much more
       * universal Spark RDD `groupByKey`. For this method to be useful with Cassandra tables, the key must
       * represent a prefix of the primary key, containing at least the partition key of the Cassandra
       * table.
       */
      public JavaPairRDD<K, Collection<V>> spanByKey() {
          return new PairRDDJavaFunctions<>(rdd()).spanByKey(kClassTag());
      }
  
      /**
       * Applies a function to each item, and groups consecutive items having the same value together.
       * Contrary to `groupBy`, items from the same group must be already next to each other in the
       * original collection. Works locally on each partition, so items from different partitions will
       * never be placed in the same group.
       */
      public <U> JavaPairRDD<U, Iterable<Tuple2<K, V>>> spanBy(
              Function<Tuple2<K, V>, U> function,
              ClassTag<U> uClassTag
      ) {
          return new PairRDDJavaFunctions<>(rdd()).spanBy(function, uClassTag);
      }
  
      /** @see {@link #spanBy(Function, ClassTag)} */
      public <U> JavaPairRDD<U, Iterable<Tuple2<K, V>>> spanBy(
              Function<Tuple2<K, V>, U> function,
              Class<U> uClass
      ) {
          return new PairRDDJavaFunctions<>(rdd()).spanBy(function, getClassTag(uClass));
      }
  
      /**
       * Counts the number of items in this RDD by selecting count(*) on Cassandra table.
       */
      public long cassandraCount() {
          return rdd().cassandraCount();
      }
  
  }
  