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Java-based middleware for in-memory processing of big data in a distributed environment.

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/*
 * 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.ignite.spark.impl

import org.apache.ignite.IgniteCache
import org.apache.ignite.configuration.CacheConfiguration
import org.apache.ignite.spark.IgniteContext
import org.apache.spark.rdd.RDD

import scala.reflect.ClassTag

abstract class IgniteAbstractRDD[R:ClassTag, K, V] (
    ic: IgniteContext,
    cacheName: String,
    cacheCfg: CacheConfiguration[K, V],
    keepBinary: Boolean
) extends RDD[R] (ic.sparkContext, deps = Nil) {
    protected def ensureCache(): IgniteCache[K, V] = {
        // Make sure to deploy the cache
        val cache =
            if (cacheCfg != null)
                ic.ignite().getOrCreateCache(cacheCfg)
            else
                ic.ignite().getOrCreateCache(cacheName)

        if (keepBinary)
            cache.withKeepBinary()
        else
            cache.asInstanceOf[IgniteCache[K, V]]
    }
}




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