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Spark personal practice series (2) -- spark service script analysis

Tag: blog http OS file 2014 Art Preface: Spark has been very popular recently. This article does not talk about spark principles, but studies how to compile spark cluster construction and service scripts. We hope to understand spark clusters from the perspective of running scripts.

Spark Source Code Analysis (a)--spark-shell analysis

Tags: AOP org jmx example init exec 2.0 lines www.1. Prepare for Work 1.1 install spark and configure spark-env.shYou need to install spark before using Spark-shell, please refer to http://www.cnblogs.com/swordfall/p/7903678.htmlIf you use only one node, you can not configure the slaves file, the

Apache Spark Technical Combat 6--Spark-submit FAQ and its solution

In addition to my consent, prohibited all reprint, emblem Shanghai one lang.ProfileAfter you have written a standalone spark application, you need to commit it to spark cluster, and generally use Spark-submit to submit your application, what do you need to be aware of in the process of using spark-submit?This article t

Spark Tutorial: Architecture for Spark

Recently saw a post on the spark architecture, the author is Alexey Grishchenko. The students who have seen Alexey blog should know that he understands spark very deeply, read his "spark-architecture" this blog, a kind of clairvoyant feeling, from the JVM memory allocation to the Spark cluster resource management, step

Spark's first research note 11 slices-Spark a brief introduction

The company launched the online project Spark has nearly 1 over time. Effective, spark in fact, excellent distributed computing platform to improve productivity.Start this note. The previous seminar Spark Research Report was shared (it will be divided into articles due to space limitations), in order to help friends who have just contacted

Spark Core Technology principle perspective one (Spark operation principle)

Original link: http://www.raincent.com/content-85-11052-1.html In the field of large data, only deep digging in the field of data science, to walk in the academic forefront, in order to be in the underlying algorithms and models to walk in front of, and thus occupy the leading position. Source: Canada Rice Valley Large dataIn the field of large data, only deep digging in the field of data science, to walk in the academic forefront, in order to be in the underlying algorithms and models to walk i

"Spark" 9. Spark Application Performance Optimization |12 optimization method __spark

1. Optimization? Why? How? When? What? "Spark applications also need to be optimized. "Many people may have this question," not already have code generators, executive optimizer, pipeline or something. ”。 Yes, Spark does have some powerful built-in tools to make your code faster when it executes. But if everything depends on the tools, framework to do, I think that can only illustrate two questions: you a

Spark's streaming and Spark's SQL easy start learning

Tags: create NTA rap message without displaying cat stream font1. What is Spark streaming?A, what is Spark streaming?Spark streaming is similar to Apache Storm, and is used for streaming data processing. According to its official documentation, Spark streaming features high throughput and fault tolerance.

Spark-spark streaming-Online blacklist filter for ad clicks

TaskOnline blacklist filter for ad clicksUsenc -lk 9999Enter some data on the data send port, such as:1375864674543 Tom1375864674553 Spy1375864674571 Andy1375864688436 Cheater1375864784240 Kelvin1375864853892 Steven1375864979347 JohnCodeImportOrg.apache.spark.SparkConfImportOrg.apache.spark.streaming.StreamingContextImportOrg.apache.spark.streaming.Seconds Object onlineblacklistfilter { defMain (args:array[string]) {/** * Step 1th: Create a Configuration object for

Spark Learning five: Spark SQL

Label:Spark Learning five: Spark SQLtags (space delimited): Spark Spark learns five spark SQL An overview Development history of the two spark Three spark SQL and hive comparison Quad

Spark Learning note--spark environment under Windows

path under the Scala installation directory is added to the system variable path, similar to the above JDK installation step), In order to verify that the installation was successful, open a new CMD window, enter it, scala and return it, if you can enter the Scala Interactive command environment, the installation is successful. As shown in the following:Note: If you cannot display version information and do not enter Scala's interactive command line, there are usually two possibilities:1. The

Spark Learning six: Spark streaming

Spark Learning six: Spark streamingtags (space delimited): Spark Spark learning six spark streaming An overview Case study of two enterprises How the three spark streaming works Application of

Apache Spark Source code reading: 13-hiveql on spark implementation

You are welcome to reprint it. Please indicate the source.Summary The SQL module was added to the newly released spark 1.0. What's more interesting is that hiveql in hive also provides good support, as a source code analysis control, it is very interesting to know how spark supports hql.Introduction to hive The following part is taken from hive in hadoop definite guide. "Hive was designed by Facebook to all

Spark Standalone mode job migrated to spark on Yarn_spark

This article mainly describes some of the operations of Spark standalone mode for job migration to spark on yarn. 1, Code RECOMPILE Because the previous Spark standalone project used the version of Spark 1.5.2, and now spark on yarn is using

Apache Spark Learning: Building spark integrated development environment with Eclipse _apache

The previous article "Apache Spark Learning: Deploying Spark to Hadoop 2.2.0" describes how to use MAVEN compilation to build spark jar packages that run directly on the Hadoop 2.2.0, and on this basis, Describes how to build an spark integrated development environment with eclipse. It is not recommended that you use E

Spark Research note 5th-Spark API Brief Introduction

Because Spark is implemented in Scala, spark natively supports the Scala API. In addition, Java and Python APIs are supported.For example, the Python API for the Spark 1.3 version. Its module-level relationships, for example, are as seen in:As you know, Pyspark is the top-level package for the Python API, which includes several important subpackages. Of1) Pyspark

2016 Big data spark "mushroom cloud" action spark streaming consumption flume acquisition of Kafka data DIRECTF mode

Liaoliang Teacher's course: The 2016 big Data spark "mushroom cloud" action spark streaming consumption flume collected Kafka data DIRECTF way job.First, the basic backgroundSpark-streaming get Kafka data in two ways receiver and direct way, this article describes the way of direct. The specific process is this:1, direct mode is directly connected to the Kafka node to obtain data.2. Direct-based approach: P

A thorough understanding of spark streaming through cases kick: spark streaming operating mechanism

Contents of this issue:  1. Spark Streaming Architecture2. Spark Streaming operating mechanism  Key components of the spark Big Data analytics framework: Spark core, spark streaming flow calculation, Graphx graph calculation, mllib machine learning,

A thorough understanding of spark streaming through cases kick: spark streaming operating mechanism and architecture

Contents of this issue:  1. Spark Streaming job architecture and operating mechanism2. Spark Streaming fault tolerant architecture and operating mechanism  In fact, time does not exist, it is by the sense of the human senses the existence of time, is a kind of illusory existence, at any time things in the universe has been happening.Spark streaming is like time, always following its running mechanism and ar

Spark Finishing (i): What Spark is and what it's capable of

first, what is spark?1. Relationship with HadoopToday, Hadoop cannot be called software in a narrow sense, and Hadoop is widely said to be a complete ecosystem that can include HDFs, Map-reduce, HBASE, Hive, and so on.While Spark is a computational framework, note that it is a computational frameworkIt can run on top of Hadoop, most of which is based on HDFsInstead of Hadoop, it replaces map-reduce in Hadoo

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