[OracleCode SF] In memory analytics with apache spark and hazelcast
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The document discusses the integration of Apache Spark with Hazelcast's in-memory data grid, highlighting the speed advantages of Spark and its fault-tolerance with resilient distributed datasets (RDDs). It provides code examples for configuration and uses cases, emphasizing parallel processing and operational benefits. Additionally, it mentions limitations regarding data updates while reading from Spark, suggesting potential issues like cursor inaccuracies.
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- 24. @gamussa @hazelcast #oraclecode Hadoop datasets run functions on each record of a file in Hadoop distributed file system or any other storage system supported by Hadoop
- 25. @gamussa @hazelcast #oraclecode What’s Hazelcast IMDG? The Fastest In-memory Data Grid
- 26. @gamussa @hazelcast #oraclecode Hazelcast IMDG is an operational, in-memory, distributed computing platform that manages data using in-memory storage, and performs parallel execution for breakthrough application speed and scale
- 27. @gamussa @hazelcast #oraclecode High-Density Caching In-Memory Data Grid Web Session Clustering Microservices Infrastructure
- 28. @gamussa @hazelcast #oraclecode What’s Hazelcast IMDG? In-memory Data Grid Apache v2 Licensed Distributed Caches (IMap, JCache) Java Collections (IList, ISet, IQueue) Messaging (Topic, RingBuffer) Computation (ExecutorService, M-R)
- 31. @gamussa @hazelcast #oraclecode final SparkConf sparkConf = new SparkConf() .set("hazelcast.server.addresses", "localhost") .set("hazelcast.server.groupName", "dev") .set("hazelcast.server.groupPass", "dev-pass") .set("hazelcast.spark.readBatchSize", "5000") .set("hazelcast.spark.writeBatchSize", "5000") .set("hazelcast.spark.valueBatchingEnabled", "true"); final JavaSparkContext jsc = new JavaSparkContext("spark://localhost:7077", "app", sparkConf); final HazelcastSparkContext hsc = new HazelcastSparkContext(jsc); final HazelcastJavaRDD<Object, Object> mapRdd = hsc.fromHazelcastMap("movie"); final HazelcastJavaRDD<Object, Object> cacheRdd = hsc.fromHazelcastCache("my- cache");
- 32. @gamussa @hazelcast #oraclecode final SparkConf sparkConf = new SparkConf() .set("hazelcast.server.addresses", "localhost") .set("hazelcast.server.groupName", "dev") .set("hazelcast.server.groupPass", "dev-pass") .set("hazelcast.spark.readBatchSize", "5000") .set("hazelcast.spark.writeBatchSize", "5000") .set("hazelcast.spark.valueBatchingEnabled", "true"); final JavaSparkContext jsc = new JavaSparkContext("spark://localhost:7077", "app", sparkConf); final HazelcastSparkContext hsc = new HazelcastSparkContext(jsc); final HazelcastJavaRDD<Object, Object> mapRdd = hsc.fromHazelcastMap("movie"); final HazelcastJavaRDD<Object, Object> cacheRdd = hsc.fromHazelcastCache("my- cache");
- 33. @gamussa @hazelcast #oraclecode final SparkConf sparkConf = new SparkConf() .set("hazelcast.server.addresses", "localhost") .set("hazelcast.server.groupName", "dev") .set("hazelcast.server.groupPass", "dev-pass") .set("hazelcast.spark.readBatchSize", "5000") .set("hazelcast.spark.writeBatchSize", "5000") .set("hazelcast.spark.valueBatchingEnabled", "true"); final JavaSparkContext jsc = new JavaSparkContext("spark://localhost:7077", "app", sparkConf); final HazelcastSparkContext hsc = new HazelcastSparkContext(jsc); final HazelcastJavaRDD<Object, Object> mapRdd = hsc.fromHazelcastMap("movie"); final HazelcastJavaRDD<Object, Object> cacheRdd = hsc.fromHazelcastCache("my- cache");
- 34. @gamussa @hazelcast #oraclecode final SparkConf sparkConf = new SparkConf() .set("hazelcast.server.addresses", "localhost") .set("hazelcast.server.groupName", "dev") .set("hazelcast.server.groupPass", "dev-pass") .set("hazelcast.spark.readBatchSize", "5000") .set("hazelcast.spark.writeBatchSize", "5000") .set("hazelcast.spark.valueBatchingEnabled", "true"); final JavaSparkContext jsc = new JavaSparkContext("spark://localhost:7077", "app", sparkConf); final HazelcastSparkContext hsc = new HazelcastSparkContext(jsc); final HazelcastJavaRDD<Object, Object> mapRdd = hsc.fromHazelcastMap("movie"); final HazelcastJavaRDD<Object, Object> cacheRdd = hsc.fromHazelcastCache("my- cache");
- 37. @gamussa @hazelcast #oraclecode DATA SHOULD NOT BE UPDATED WHILE READING FROM SPARK
- 39. @gamussa @hazelcast #oraclecode MAP EXPANSION SHUFFLES THE DATA INSIDE THE BUCKET
- 40. @gamussa @hazelcast #oraclecode CURSOR DOESN’T POINT TO CORRECT ENTRY ANYMORE, DUPLICATE OR MISSING ENTRIES COULD OCCUR
- 42. @gamussa @hazelcast #oraclecode THANKS! Any questions? You can find me at @gamussa [email protected]