hadoop job description

Part 1: core-site.xml • core-site.xml is the core attribute file of hadoop, the parameter is the core function of hadoop, independent of HDFS and mapreduce. Parameter List • FS. default. name • default value File: // • Description: sets the hostname and port of the hadoop namenode. The default value is standalone mode.

Preface The most interesting thing about hadoop is hadoop Job Scheduling. Before introducing how to set up hadoop, it is necessary to have a deep understanding of hadoop job scheduling. We may not be able to use

computing bottleneck. The example is as follows: This figure is based on the above description, and I believe it should be easy for everyone to understand. So since the actual process of hadoop is Case 2, why should I first describe case 1? There are two reasons: 1. Situation 1 is easier to understand. 2. Case 1 is easierImplementation. Based on hadoop's scheduling principle,Write your own cluster sched

in Hadoop, the MapReduce job ID is in the format job_201412081211_0002. This indicates that the job is the second job (the job number starts at 0001) and the job starts on December 8, 2014 12:11. a task belongs to the

I. Job input and output optimizationUse Muti-insert, union All, the union all of the different tables equals multiple inputs, union all of the same table, quite map outputExample　　Second, data tailoring2.1. Column ClippingWhen hive reads the data, it can query only the columns that are needed, ignoring the other columns. You can even use an expression that is being expressed.See. Http://www.cnblogs.com/bjlhx/p/6946202.html2.2. Partition clippingReduce

Detailed description of hadoop operating principles and hadoop principles Introduction HDFS (Hadoop Distributed File System) Hadoop Distributed File System. It is based on a paper published by google. The paper is a GFS (Google File System) Google File System (Chinese and En

What is the role of 1.Combiner? 2. How are job level parameters tuned? 3. What are the tasks and administrator levels that can be tuned? Hadoop provides a variety of configurable parameters for user jobs to allow the user to adjust these parameter values according to the job characteristics to optimize the operational efficiency.an application authoring specifica

Hadoop provides a variety of configurable parameters for user jobs to allow the user to adjust these parameter values according to the job characteristics to optimize the operational efficiency.an application authoring specification1. Set CombinerFor a large number of MapReduce programs, if you can set a combiner, it is very helpful to improve the performance of the job.Combiner reduces the result of the Ma

not bottlenecks unless the computing logic is very complex. Therefore, compressing intermediate results is usually beneficial. The following is a comparison of the data volume between the wordcount intermediate result compressed and the map intermediate result generated without compression local disk read/write: The intermediate map result is not compressed: Compress the intermediate map result: We can see that the results of the same job and data

to reduce. When the reduce computing logic consumes a large amount of memory, data can be cached in part of the memory, reduce memory is idle.2.2 reduce side parameter optimization Option Type Default Value Description Mapred. Reduce. Parallel. Copies Int 5 Maximum number of threads that can be concurrently downloaded by each reduce. Mapred. Reduce. Copy. Backoff Int 300 Maximum

Application Development Technology detailed description [1] Author: Liu Gang Publishing House: Mechanical Industry Publishing House published at: 2014-01-01i s B N: 9787111452447 price: $79.002 preface to book directory editing Chapter 1 hadoop Overview 1.1 hadoop Origin 1.1.1 Google and hadoop modules 1.1.2 why

Http://www.cnblogs.com/spork/archive/2010/04/21/1717552.html The previous analysis is only a prelude to Hadoop job submission. The actual job submission code is in the main of the MR program. RunJar will dynamically call this main at the end. In (2). What we need to do below is to go further than RunJar so that job sub

compressed, you can also choose to compress ??? The compression formats supported by Hadoop include GzipCodec, LzoCodec, BZip2Codec, and LzmaCodec. Generally, LzoCodec is suitable for balanced cpu and disk compression ratios. But it also depends on the specific situation of the job. If you want to select the compression algorithm for the intermediate result, you can set the configuration parameters:Mapred.

are similar. The second type is hadoop data engineers who are mainly responsible for data processing and implementing mapreduce algorithms. As enterprise hadoop applications grow, engineers with Java, C ++, and other programming experience will find more opportunities. The third category is hadoop data administrators who usually have professional data scien

When using Windows to invoke the Hadoop yarn platform, you will generally encounter the following error:2014-05-28 17:32:19,761 WARN org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor:Exception from Container-launch with container id:container_1401177251807_0034_01_000001 and exit Code:1org.apache.hadoop.util.shell$exitcodeexception:/bin/bash:line 0: Fg:no Job Control at Org.apache.hadoop.ut

hadoop-1.2.1 Pseudo-distributed set up, but also just run through the Hadoop-example.jar package wordcount, all this looks so easy.But unexpectedly, his own Mr Program, run up to encounter the no job file jar and classnotfoundexception problems.After a few twists and ends, the MapReduce I wrote was finally successfully run.I did not add a third-party jar package

In hadoop, mapreduce Java jobs usually start with writing Mapper and reducer, create a job object, and then use the set method of the object to set Mapper and reducer and parameters such as input and output, finally, call the waitforcompletion (true) method of the job object to submit the job and wait for the

), a list (9,11,13), or a wildcard character (*). Because 4 and 6 of these two elements are mutually exclusive, they should be set by a question mark (?). To indicate the field that you do not want to set, "/" if the combination of values represents the number of repetitions (10/6 means repeat 6 times every 10 seconds).Start timerProperty>Bean>The Triggers property accepts a set of triggers."0 0 12 * *?" trigger 12 o'clock noon every day."0 15 10?" * * "trigger 10:15 every day""0 15 10 * *?" Dai

Hadoop is a distributed system infrastructure under the Apache Foundation. It has two core components: Distributed File System HDFS, which stores files on all storage nodes in the hadoop cluster; it consists of namenode and datanode. the distributed computing engine mapreduce is composed of jobtracker and tasktracker. Hadoop allows you to easily develop distrib

Symptom:After a job is submitted, it is always run on the local machine and cannot be submitted to Hadoop job tracker.Http: // 192.168.1.130: 50030/jobtracker. jsp. The running job cannot be viewed. In the console output: 14/02/15 00:04:20 INFO mapred. LocalJobRunner: reduce> sort Cause analysis: First Attempt:Replace