Step 1: software required by the spark cluster;
Build a spark cluster on the basis of the hadoop cluster built from scratch in Articles 1 and 2. We will use the spark 1.0.0 version released in May 30, 2014, that is, the latest version of spark, to build a spark Cluster Based
Start and view the cluster status
Step 1: Start the hadoop cluster, which is explained in detail in the second lecture. I will not go into details here:
After the JPS command is run on the master machine, the following process information is displayed:
When JPS is used on slave1 and slave2, the following process information is displayed:
Step 2: Start the spark Cluster
On the basis of the successful start of the hadoop cluster, to start the
spark to better support mobile devices such as mobile phones. Hashjoin, one of Databricks's founders, revealed the refactoring approach: using the Scala.js project to compile the spark code into JavaScript and then use Safari/chrome to execute on the phone. A code can support Android/ios. However, considering the performance relationship, it may be necessary to rewrite the underlying network module to supp
Install spark
Spark must be installed on the master, slave1, and slave2 machines.
First, install spark on the master. The specific steps are as follows:
Step 1: Decompress spark on the master:
Decompress the package directly to the current directory:
In this case, create the spa
Step 1: Test spark through spark Shell
Step 1:Start the spark cluster. This is very detailed in the third part. After the spark cluster is started, webui is as follows:
Step 2:Start spark shell:
In this case, you can view the shell in the following Web console:
Step 3:Co
Install spark
Spark must be installed on the master, slave1, and slave2 machines.
First, install spark on the master. The specific steps are as follows:
Step 1: Decompress spark on the master:
Decompress the package directly to the current directory:
In this case, create the
platform. Some Hadoop tools can also run MapReduce tasks directly without programming. Xplenty is a Hadoop-based data integration service and does not require any programming or deployment.Although Hive provides a command-line interface, MapReduce does not have an interactive mode. Projects such as Impala,presto and Tez are trying to provide a fully interactive query pattern for Hadoop.In terms of installation and maintenance, Spark is not tied to Ha
Tags: spark books spark hotspot Spark Technology spark tutorial
The command to end historyserver is as follows:
Step 4: Verify the hadoop distributed Cluster
First, create two directories on the HDFS file system. The creation process is as follows:
/Data/wordcount in HDFS is used to store the data f
1. Local Operation error and solutionWhen you run the following command:./bin/spark-submit --class Org.apache.spark.examples.mllib.JavaALS --master local[*] /opt/cloudera/ Parcels/cdh-5.1.2-1.cdh5.1.2.p0.3/lib/hadoop-yarn/lib/spark-examples_2.10-1.0.0-cdh5.1.2.jar /user/data/ Netflix_rating 10/user/data/resultThe following error will appear:Exception in t
command:Add the following content, including the bin directory to the pathMake it effective with source1.4 Verification
The input Scala version can be displayed as follows:Scala can also be programmed directly with Scala:2. Install Spark 2.1 Downloads Spark
Download Address:Http://spark.apache.org/downloads.htmlFor learning purposes, I downloaded the pre-compiled version 1.6.2.2 Decompression
The download
Next package, use Project structure's artifacts:Using the From modules with dependencies:Select Main Class:Click "OK":Change the name to Sparkdemojar:Because Scala and spark are installed on each machine, you can delete both Scala and spark-related jar files:Next Build:Select "Build Artifacts":The rest of the operation is to upload the jar package to the server, and then execute the
Next package, use Project structure's artifacts:Using the From modules with dependencies:Select Main Class:Click "OK":Change the name to Sparkdemojar:Because Scala and spark are installed on each machine, you can delete both Scala and spark-related jar files:Next Build:Select "Build Artifacts":The rest of the operation is to upload the jar package to the server, and then execute the
Create a Scala idea project:Click "Next":Click "Finish" to complete the project creation:To modify an item's properties:First modify the Modules option:Create two folders under SRC and change their properties to source:Then modify the libraries:Because you want to develop the spark program, you need to bring in the jar packages that spark needs to develop:After the import package is complete, create a packa
Create a Scala idea project:Click "Next":Click "Finish" to complete the project creation:To modify an item's properties:First modify the Modules option:Create two folders under SRC and change their properties to source:Then modify the libraries:Because you want to develop the spark program, you need to bring in the jar packages that spark needs to develop:After the import package is complete, create a packa
Introduction to spark Basics, cluster build and Spark ShellThe main use of spark-based PPT, coupled with practical hands-on to enhance the concept of understanding and practice.Spark Installation DeploymentThe theory is almost there, and then the actual hands-on experiment:Exercise 1 using Spark Shell (native mode) to
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Next, use mr-jobhistory-daemon.sh to start jobhistory Server:
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After startup, you can view the task execution history in jobhistory on the Web Console through http: // spar
Output query results, sequentially accessing the columns of the result row.Teenagers.map (t = "Name:" + t (0)). Collect (). foreach (println)Sc.stop ()}}As shown above, Spark SQL provides a very friendly SQL interface to interact with data from a variety of different data sources, and the syntax used is also well-known by the team for SQL query syntax. This is useful for non-technical project members, such as data analysts and database administrators
This article focuses on some of the typical problems I have encountered since using spark and how to solve them, hoping to help the students who meet the same problem.1. Spark environment or configuration relatedQ:in the Spark Client Profile spark-defaults.conf, how should spark.executor.memory and Spark.cores.max be c
Step 4: build and test the spark development environment through spark ide
Step 1: Import the package corresponding to spark-hadoop, select "file"> "project structure"> "Libraries", and select "+" to import the package corresponding to spark-hadoop:
Click "OK" to confirm:
Click "OK ":
After idea
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