avro spark

Spark standalone cluster is a cluster mode in the master-slaves architecture. Like most master-slaves cluster clusters, there is a single point of failure (spof) in the master node. Spark provides two solutions to solve this single point of failure problem: Single-node recovery with local file system) Zookeeper-based standby Masters (standby masters with zookeeper) Zookeeper provides a leader election m

1. Official website Download source code, address: http://spark.apache.org/downloads.html2. Use MAVEN to compile:Note Before you translate, you need to set the Java heap size and the permanent generation size to avoid MVN memory overflow.Under Windows Settings:%maven_home%\bin\mvn.cmd, place one of theAdd a row below this line of commentsSet maven_opts=-xmx2048m-xx:permsize=512m-xx:maxpermsize=1024mTo compile laterPackageWhen the compilation is complete, import the project into IntelliJFile->imp

Below is a look at the use of Union:Use the collect operation to see the results of the execution:Then look at the use of Groupbykey:Execution Result:The join operation is the process of a Cartesian product operation, as shown in the following example:To perform a join operation on RDD3 and RDD4:Use collect to view execution results:It can be seen that the join operation is exactly a Cartesian product operation;The reduce itself, which is an action-type operation in an RDD operation, causes the

the manager.For hash Based Shuffle, see Org.apache.spark.shuffle.FileShuffleBlockManager; for sort Based Shuffle, Please see Org.apache.spark.shuffle.IndexShuffleBlockManager.1.1.4 Org.apache.spark.shuffle.ShuffleReaderShufflereader implements the logic of how the downstream task reads the shuffle output of the upstream shufflemaptask. This logic is more complex, In simple terms, you get the location information of the data through Org.apache.spark.MapOutputTracker, and then if the data is loca

Run the example one by one to see the results illustrate Hadoop_home environment variablesOrg.apache.spark.examples.sql.hive.JavaSparkHiveExampleModify the run Configuration to add env hadoop_home=${hadoop_home}Run the Java class. After the hive example is exhausted, delete the metastore_db directory.Here's a simple way to run it one by oneEclipse->file->import->run/debug Launch ConfigurationBrowse to the Easy_dev_labs\runconfig directory. Import all.Now from Eclipse->run->run ConfigurationStart

First of all, of course, is to download a spark source code, in the http://archive.cloudera.com/cdh5/cdh/5/to find their own source code, compiled their own packaging, about how to compile packaging can refer to my original written article: http://blog.csdn.net/xiao_jun_0820/article/details/44178169 After execution you should be able to get a compressed package similar to SPARK-1.6.0-CDH5.7.1-BIN-CUSTOM-SP

hive, Spark SQL supports any storage format supported by hive (SerDe), including files, Rcfiles, ORC, parquet, Avro, and Protocol Buffer (of course Spark SQL can also read these files directly). To connect to a deployed hive, you need to copy Hive-site.xml, Core-site.xml, Hdfs-site.xml to Spark's./conf/Directory If you do not want to connect to an existing hive,

│ │ └── data.parquet │ ... └── gender=female ... │ ├── country=US │ └── data.parquet ├── country=CN │ └── data.parquet ...Using SQLContext.read.parquet or SQLContext.read.load entering path path/to/table, Spark SQL can automatically extract partition information from the path. The schema of the returned Dataframe becomes:stringtruelongtruestrin

This article from the official blog, slightly added: https://github.com/mesos/spark/wiki/Spark-Programming-GuideSpark sending Guide From a higher perspective, in fact, every Spark application is a Driver class that allows you to run user-defined main functions and perform various concurrent operations and calculations on the cluster. The most important abstracti

Start Hadoop and start Spark.Build a simple test data customers.txt, for convenience, I put it in the Spark/bin directory:John Smith, Austin, TX, 78727200, Joe Johnson, Dallas, TX, 75201300, Bob Jones, Houston, TX, 77028400, Andy Davis, Sa n Antonio, TX, 78227500, James Williams, Austin, TX, 78727Start Spark-sql:./spark-sql.sh　　Map data into a database table:Load

There are two ways, one is sparkstreaming in the driver from listening, flume to push the data, the other is sparkstreaming according to the time policy rotation to flume pull data.At first I thought there was only the first method, but the Nima problem is that driver up the knot is flaky, so every time I restart streaming found that every time to change the flume, the egg pain died, later found there is the method, OK, the different method code written out, Actually, it doesn't change much. (Th

Spark is a class mapred computing framework developed by UC Berkeley Amplab. The Mapred framework applies to batch jobs, but because of its own framework constraints, first, pull-based heartbeat job scheduling. Second, the shuffle intermediate results all landed disk, resulting in high latency, start-up overhead is very large. And the spark is for iterative, interactive computing generation. First, it uses

As a memory-based distributed computing engine, Spark's memory management module plays a very important role in the whole system. Understanding the fundamentals of spark memory management helps to better develop spark applications and perform performance tuning. The purpose of this paper is to comb out the thread of Spark memory management, and draw the reader's