Cache, 将RDD在第一次使用后保存在memory里面, 以便于后面反复使用, 并当memory不够时, 会将部分RDD spill到磁盘, 牺牲效率来保证可用性 Disk persistence, 可以通过设置persist flag来将选择将RDD persist到disk 用户定义RDD spill优先级, set a persistence priority on each RDD to specify which in-memory dat...
Our scheduler assigns tasks to machines based on datalocality using delay scheduling [32]. If atask needstoprocess apartitionthat is availablein memory on a node,wesend it to that node. Otherwise, if a task processesa partition for which the containing RDD provides preferred locations (e.g.,...
1 It primarily achieves this by caching data required for computation in the memory of the nodes in the cluster. In-memory cluster computation enables Spark to run iterative algorithms, as programs can checkpoint data and refer back to it without reloading it from disk; in addition, it ...
Spark1 targets a specific subset of these applications: those that reuse a working set of data across multiple rounds of computation. These applications fall in one of three categories: Iterative jobs: Many algorithms (for example, most machine learning) fall in this category. Although MapReduce ...
Executor : A process launched for an application on a worker node, that runs tasks and keeps data in memory or disk storage across them. Each application has its own executors. Task: A unit of work that will be sent to one executor Job : A parallel computation consisting of multiple tasks...
An in-memory distributed computing system; Apache Spark is often used to speed up big data applications. It caches intermediate data into memory, so there is no need to repeat the computation or reload data from disk when reusing these data later. This mechanism of caching data in memory ...
Memory Tuning (内存调优) Fault-tolerance Semantics (容错语义) 快速链接 概述 Spark Streaming 是 Spark Core API 的扩展, 它支持弹性的, 高吞吐的, 容错的实时数据流的处理. 数据可以通过多种数据源获取, 例如 Kafka, Flume, Kinesis 以及 TCP sockets, 也可以通过例如 map, reduce, join, window 等的高级...
--executor-memory 1g \ --total-executor-cores 2 1. 2. 3. 4. 读取spark安装目录下的readme.md文件,并统计词条数量和显示第一行字符。 scala> val textFile = sc.textFile("hdfs://hadoop01:8020/test/input/README.md") //读取readme.md文件 ...
MemoryPools是MemoryManager用来跟踪存储和执行之间内存划分的薄记抽象。 如图: MemoryManager的两种实现: There are two implementations of org.apache.spark.memory.MemoryManager which vary in how they handle the sizing of their memory pools: - org.apache.spark.memory.UnifiedMemoryManager, the default in S...
Memory Management and Binary Processing: off-heap管理内存,降低对象的开销和消除JVM GC带来的延时。 Cache-aware computation: 优化存储,提升CPU L1/ L2/L3缓存命中率。 Code generation: 优化Spark SQL的代码生成部分,提升CPU利用率。 Tungsten设计并实现了一种叫做Unsafe Row的二进制数据结构。Unsafe Row本质上是...