__SparkContext__是spark功能的主要入口。 其代表与spark集群的连接，能够用来在集群上创建RDD、累加器...
String[] ns = fqname.split("\\.");//TODO:Handle also compressed filesList<FileSplit> nlif = NLineInputFormat.getSplitsForFile(fst, sc.hadoopConfiguration(), splitlen); JavaRDD<FileSplit> splitRDD = sc.parallelize(nlif); splitRDD.foreach( split -> { FastqRecordReader fqreader =newFast...
parallelize(Arrays.asList(1, 1, 2, 3, 5, 8, 13)); Function<Tuple2<Integer, Integer>, Boolean> areOdd = x -> (x._1() % 2 == 0) && (x._2() % 2 == 0); JavaPairRDD<Integer, Integer> pairRDD = rdd.zip(rdd); JavaPairRDD<Boolean, Iterable<Tuple2<Integer, Integer>>>...
parallelize(l, slices); int count = dataSet.map(i -> { double x = Math.random() * 2 - 1; double y = Math.random() * 2 - 1; return (x * x + y * y < 1) ? 1 : 0; }).reduce((i1, i2) -> i1 + i2); double pi = 4.0 * (double) count / (double) n; ...
/** Default level of parallelism to use when not given by user (e.g. parallelize and makeRDD). */ def defaultParallelism: java.lang.Integer = sc.defaultParallelism /** Default min number of partitions for Hadoop RDDs when not given by user */ ...
__SparkContext__是spark功能的主要入口。 其代表与spark集群的连接，能够用来在集群上创建RDD、累加器...
Broadcast<CachedS3ClientFactory> clientFactory = sc.broadcast(newCachedS3ClientFactory());// Get the inventory report, split it into lines, parse each line to a POJO,// Filter, and write new csv file to S3JavaRDD<InventoryManifest.Locator> locatorRDD = sc.parallelize(manifest.getLocators())...
.parallelize(Arrays.asList(0)) .map(new Function<Integer, Tuple2<List<Row>, StructType>>() { @Override public Tuple2<List<Row>, StructType> call(Integer v1) throws Exception { Tuple2<List<Row>, StructType> tuple = new ExponentialBackoffRetryPolicy<Tuple2<List<Row>, StructType>>(3, 100...
parallelize(Arrays.asList(1, 2, 3, 4)); JavaRDD<Integer> result = rdd.map( new Function<Integer, Integer>() { public Integer call(Integer x) { return x*x;}}); System.out.println(StringUtils.join(result.collect(), ",")); } } 代码示例来源:origin: databricks/learning-spark public ...
Broadcast<CachedS3ClientFactory> clientFactory = sc.broadcast(newCachedS3ClientFactory());// Get the inventory report, split it into lines, parse each line to a POJO,// Filter, and write new csv file to S3JavaRDD<InventoryManifest.Locator> locatorRDD = sc.parallelize(manifest.getLocators())...