spark webinars

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

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

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

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

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

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

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

Article Source: http://www.dataguru.cn/thread-331456-1-1.html Today you want to make an error in the Yarn-client state of Spark-shell:[Python] View plaincopy [Hadoop@localhost spark-1.0.1-bin-hadoop2]$ Bin/spark-shell--master yarn-client Spark Assembly has been Built with Hive, including DataNucleus jars on classpath

You are welcome to reprint it. Please indicate the source, huichiro.Summary Yarn in hadoop2 is a management platform for distributed computing resources. Due to its excellent model abstraction, it is very likely to become a de facto standard for distributed computing resource management. Its main responsibility is to manage distributed computing clusters and manage and allocate computing resources in clusters. Yarn provides good implementation standards for application development.

Welcome reprint, Reproduced please indicate the source.ProfileThis article briefly describes how to use Spark-cassandra-connector to import a JSON file into the Cassandra database, a comprehensive example that uses spark.Pre-conditionsSuppose you have read the 3 of technical combat and installed the following software Jdk Scala SBt Cassandra Spark-cassandra-connector Experiment

This article is mainly from two aspects:Contents of this issue1 exactly Once2 output is not duplicated1 exactly OnceTransaction:　　Bank Transfer For example, a user to transfer to the User B, if the B users confiscated, or received multiple accounts, is to undermine the consistency of the transaction. Transactions are handled and processed only once, that is, a is only turned once and B is only received once.　　Decrypt the sparkstreaming schema from a transactional perspective:　　The sparkstreaming

Learn Spark 2.0 (new features, real projects, pure Scala language development, CDH5.7)Share the network disk download--https://pan.baidu.com/s/1c2f9zo0 password: pzx9Spark entered the 2.0 era, introducing many excellent features, improved performance, and more user-friendly APIs. In the "unified programming" is very impressive, the implementation of offline computing and Flow computing API unification, the implementation of the

[Spark] [Python]spark example of obtaining Dataframe from Avro fileGet the file from the following address:Https://github.com/databricks/spark-avro/raw/master/src/test/resources/episodes.avroImport into the HDFS system:HDFs Dfs-put Episodes.avroRead in:Mydata001=sqlcontext.read.format ("Com.databricks.spark.avro"). Load ("Episodes.avro")Interactive Run Results:In

Spark Learning III: Installing and Importing source code for spark schedule and ideatags (space delimited): Spark Spark learns to install and import source code for three spark schedule and idea Data location during an RDD operation Two

The content of this lecture:A. Jobscheduler Insider implementationB. Jobscheduler Deep ThinkingNote: This lecture is based on the spark 1.6.1 version (the latest version of Spark in May 2016).Previous section ReviewLast lesson, we take the Jobgenerator class as the center of gravity, for everyone left and right extension, decryption job dynamic generation, and summed up the job dynamic generation of the thr

The spark kernel is developed by the Scala language, so it is natural to develop spark applications using Scala. If you are unfamiliar with the Scala language, you can read Web tutorials A Scala Tutorial for Java programmers or related Scala books to learn. This article will introduce 3 Scala spark programming examples, WordCount, TOPK, and Sparkjoin, representi

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

Transferred from: http://www.cnblogs.com/hseagle/p/3664933.htmlWedgeSource reading is a very easy thing, but also a very difficult thing. The easy is that the code is there, and you can see it as soon as you open it. The hard part is to understand the reason why the author should have designed this in the first place, and what is the main problem to solve at the beginning of the design.It's a good idea to read the spark paper from Matei Zaharia, befor

It is believed that many people will encounter Task not serializable when they start using spark, most of which are caused by calling an object that cannot be serialized in the RDD operator. Why must the objects in the incoming operator be serialized? This is going to start with spark itself, Spark is a distributed computing framework, the RDD (resilient distribu