我们提出通过一个通用接口来表示每个RDD,该接口包含以下5个重要部分: 1. a set of partitions:数据集的原子部分 2. a set of dependencies on parent RDDs 对父RDDs的依赖关系 3. 一个通过基于父RDDs计算数据集的函数 4. 分区方式的元数据 5. 数据存放位置的元数据。 例如:表示一个HDFS文件的RDD中的每个...
We propose a distributed memory abstraction called resilient distributed datasets (RDDs) that supports applications with working sets while retaining the attractive properties of data flow models: automatic fault tolerance, locality-aware scheduling, and scalability. RDDs allow users to explicitly cache wo...
另外, 编程者可以通过调用 RDDs 的 persist 方法来缓存后续需要复用的 RDDs. Spark 默认是将缓存数据放在内存中, 但是如果内存不足的话则会写入到磁盘中. 用户可以通过 persist 的参数来调整缓存策略, 比如只将数据存储在磁盘中或者复制备份数据到多台机器. 最后, 用户可以为每一个 RDDs 的缓存设置优先级, 以...
我们想把首行去掉,返回新RDD是withoutTitleLinesvalwithoutTitleLines=lines.filter(!_. contains("age"))//3.将每行数据以;分割下,返回名字是lineOfData的新RDDvallineOfData=withoutTitleLines.map(_.split(";"))//4.将lineOfData缓存到内存到,并设置缓存...
2: Resilient Distributed Datasets(RDDs) 这节主要讲述 RDDs 的概要, 首先定义 RDDs(2.1)以及介绍 RDDs 在 spark 中的编程接口(2.2), 然后对 RDDs 和细粒度共享内存抽象进行的对比(2.3).最后我们讨论了 RDD 模型的限制性. 2.1 RDD 抽象 一个RDD 是一个只读, 被分区的数据集.我们可以通过两种对稳定的存...
This chapter covers the oldest foundational concept in Spark called resilient distributed datasets (RDDs). To truly understand how Spark works, you must understand the essence of RDDs. They provide an extremely solid foundation that other abstractions are built upon. The ideas behind RDDs are ...
We present Resilient Distributed Datasets (RDDs), a dis- tributed memory abstraction that lets programmers per- form in-memory computations on large clusters in a fault-tolerant manner. RDDs are motivated by two types of applications that current computing frameworks han- dle inefficiently: iterati...
resilient distributed datasets 读后笔记 1.Formally, an RDD is a read-only, partitioned collection of records. RDDs can be only created through deterministic operations on either (1) a dataset in stable storage or (2) other existing RDDs....
ResilientDistributedDatasets(RDDs) •Restrictedformofdistributedsharedmemory –read-only,partitionedcollectionofrecords –canonlybebuiltthroughcoarse‐grained deterministictransformations •datainstablestorage •transformationsfromotherRDDs. •Expresscomputationby –definingRDDs 4 FaultRecovery •Efficientfault...
A Tale of Three Apache Spark APIs: RDDs vs DataFrames and Datasets Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing Research Paper Back to Glossary Databricks Inc. 160 Spear Street, 15th Floor San Francisco, CA 94105 ...