Hadoop | 易学教程

必备干货 | Hbase简介以及数据结构和表详解

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注：此文章内容均节选自充电了么创始人，CEO兼CTO陈敬雷先生的新书《分布式机器学习实战》（人工智能科学与技术丛书）【陈敬雷编著】【清华大学出版社】文章目录前言 Hbase原理和功能介绍 1. Hbase特性 2. Hbase的架构核心组件 Hbase数据结构和表详解总结前言 Hbase 经常用来存储实时数据，比如Storm/Flink/Spark-Streaming消费用户行为日志数据进行处理后存储到Hbase，通过Hbase的API也能够毫秒级别的实时查询。如果是对Hbase做非实时的离线数据统计，我们可以通过Hive建一个到Hbase的映射表，然后写Hive SQL来对Hbase的数据进行统计分析。并且这种方式可以方便的和其它的Hive表做关联查询，做更复杂的统计。所以从交互形势上Hbase满足了实时和离线的应用场景，在互联网公司应用的也非常普遍。 Hbase原理和功能介绍 HBase是一个分布式的、面向列的开源数据库，该技术来源于 Fay Chang 所撰写的Google论文“Bigtable：一个结构化数据的分布式存储系统”。就像Bigtable利用了Google文件系统（File System）所提供的分布式数据存储一样，HBase在Hadoop之上提供了类似于Bigtable的能力。HBase是Apache的Hadoop项目的子项目

Change the size of random data generation on Hadoop

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问题 I am running sort example on Hadoop using RandomWriter function. This particular function writes 10 gig (by default) of random data/host to DFS using Map/Reduce. bin/hadoop jar hadoop-*-examples.jar randomwriter <out-dir>. Can anyone please tell how can I change the size 10GB of RandomWriter function? 回答1: That example have some configurable parameters. These parameters are given to jar in a config file. To run use it as (suppling a config file) bin/hadoop jar hadoop-*-examples.jar

Programmatically get progress rate of Hadoop's tasks

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问题 For research reasons, I would like to record the progress rate of all tasks in order to analyse the progress rates evolve over time. I already managed to recompile these JARs in order to log latency of heartbeat packets: hadoop-yarn-server-common-3.2.0.jar hadoop-yarn-server-nodemanager-3.2.0.jar hadoop-yarn-server-resourcemanager-3.2.0.jar Initially, I thought the progress rate information of each task would be part of the heartbeat packet sent to the ResourceManager . However, by looking at

Spark Scala S3 storage: permission denied

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问题 I've read a lot of topic on Internet on how to get working Spark with S3 still there's nothing working properly. I've downloaded : Spark 2.3.2 with hadoop 2.7 and above. I've copied only some libraries from Hadoop 2.7.7 (which matches Spark/Hadoop version) to Spark jars folder: hadoop-aws-2.7.7.jar hadoop-auth-2.7.7.jar aws-java-sdk-1.7.4.jar Still I can't use nor S3N nor S3A to get my file read by spark: For S3A I have this exception: sc.hadoopConfiguration.set("fs.s3a.access.key",

MapReduce Hadoop on Linux - Multiple data on input

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问题 I am using Ubuntu 20.10 on Virtual Box and Hadoop version 3.2.1 (if you need any more info comment me). My output at this moment gives me this : Aaron Wells Peirsol ,M,17,United States,Swimming,2000 Summer,0,1,0 Aaron Wells Peirsol ,M,21,United States,Swimming,2004 Summer,1,0,0 Aaron Wells Peirsol ,M,25,United States,Swimming,2008 Summer,0,1,0 Aaron Wells Peirsol ,M,25,United States,Swimming,2008 Summer,1,0,0 For the above output I would like to be able to sum all of his medals (the three

基于Storm构建实时热力分布项目实战

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基于Storm构建实时热力分布项目实战下载地址：百度云盘 Storm是实时流处理领域的一柄利器，本课程采用最新的Storm版本1.1.0，从0开始由浅入深系统讲解，深入Storm内部机制，掌握Storm整合周边大数据框架的使用，从容应对大数据实时流处理！适合人群及技术储备要求这是一门非常具有可操作性的课程，适合Java工程师正处于瓶颈期想提升自己技术、想转型做大数据的开发者，更适合对于大数据感兴趣、想从事大数据研发工作的同学。本课程将手把手带你从零循序渐进地讲解Storm各方面的技术点，让你轻松胜任实际大数据实时流处理的工作，稳拿高薪！技术储备要求熟练掌握Java SE、Linux即可课程目录：第1章课程导学引见课程相关背景，学习建议等等1-1 -导学试看1-2 -OOTB环境运用演示1-3 -授课习气与学习建议第2章初识实时流处置StormStorm作爲近几年Hadoop生态圈很火爆的大数据实时流处置框架，是成爲大数据研发工程师必备的技艺之一。本章将从如下几个方面让大家关于Storm有微观上的看法：什麼是Storm、Storm的展开史、Storm比照Hadoop的区别、Storm比照Spark Streaming的区别、Storm的劣势、Storm运用现状及展开趋向、Storm运用案例分享...2-1 -课程目录2-2 -Storm是什麼2-3

How to move Amazon S3 objects into partitioned directories

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问题 Take for example an s3 bucket with the following structure with files of the form francescototti_yyyy_mm_dd_hh.csv.gz: For example: francescototti_2019_05_01_00.csv.gz, francescototti_2019_05_01_01.csv.gz, francescototti_2019_05_01_02.csv.gz, ..... francescototti_2019_05_01_23.csv.gz, francescototti_2019_05_02_00.csv.gz Each hourly file is about 30 MB. I would like the final hive table to be partitioned by day stored as orc files. What is the best way to do this? I imagine a few ways,

Sqoop import job error org.kitesdk.data.ValidationException for Oracle

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问题 Sqoop import job for Oracle 11g fails with error ERROR sqoop.Sqoop: Got exception running Sqoop: org.kitesdk.data.ValidationException: Dataset name 81fdfb8245ab4898a719d4dda39e23f9_C46010.HISTCONTACT is not alphanumeric (plus '_') here's the complete command: $ sqoop job --create ingest_amsp_histcontact -- import --connect "jdbc:oracle:thin:@<IP>:<PORT>/<SID>" --username "c46010" -P --table C46010.HISTCONTACT --check-column ITEM_SEQ --target-dir /tmp/junk/amsp.histcontact -as-parquetfile -m 1

Sqoop import job error org.kitesdk.data.ValidationException for Oracle

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Spark Small ORC Stripes

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问题 We use Spark to flatten out clickstream data and then write the same to S3 in ORC+zlib format, I have tried changing many settings in Spark but still the resultant stripe sizes of the ORC file getting created are very small (<2MB) Things which I tried so far to decrease the stripe size, Earlier each file was 20MB in size, using coalesce I am now creating files which are of 250-300MB in size, but still there are 200 stripes per file i.e each stripe <2MB Tried using hivecontext instead of