Recently, after listening to Liaoliang's 2016 Big Data spark "mushroom cloud" action, Flume,kafka and spark streaming need to be integrated.Feel a moment difficult to get started, or start from the simple: my idea is that, flume produce data, and then output to spark streaming,flume source data is netcat (address: localhost, port 22222), The output is
The main contents of this section
Hadoop Eco-Circle
Spark Eco-Circle
1. Hadoop Eco-CircleOriginal address: http://os.51cto.com/art/201508/487936_all.htm#rd?sukey= a805c0b270074a064cd1c1c9a73c1dcc953928bfe4a56cc94d6f67793fa02b3b983df6df92dc418df5a1083411b53325The key products in the Hadoop ecosystem are given:Image source: http://www.36dsj.com/archives/26942The following is a brief introduction to the products1 HadoopApache's Hadoop p
1, first download the image to local. https://hub.docker.com/r/gettyimages/spark/~$ Docker Pull Gettyimages/spark2, download from https://github.com/gettyimages/docker-spark/blob/master/docker-compose.yml to support the spark cluster DOCKER-COMPOSE.YML fileStart it$ docker-compose Up$ docker-compose UpCreating spark_master_1Creating spark_worker_1Attaching to Sp
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:
S
Spark Communication Module
1, Spark Cluster Manager can have local, standalone, mesos, yarn and other deployment methods, in order to
Centralized communication mode
1, RPC remote produce call
Spark Communication mechanism:
The advantages and characteristics of Akka are as follows:
1, parallel and distributed: Akka in design with asynchronous communication and dis
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
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
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
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
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
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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
method makes it compatible with both batch and real-time data processing logic and algorithms. Facilitates some specific applications that require joint analysis of historical and real-time data.Bagel:pregel on Spark, which can be calculated using spark, is a very useful small project. Bagel comes with an example that implements Google's PageRank algorithm.What the hell is Hadoop,hbase,storm,
Recently, in the Test Flume combines Kafka with spark streaming experiments. Today, the simple combination of flume and spark to make a record here, to avoid users detours. There are not thoughtful places also want to pass by the great God a lot of advice.The experiment is relatively simple, divided into two parts: first, Use avro-client send data two, Use Netcat
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