hdfs big data

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"Big Data dry" implementation of big data platform based on Hadoop--Overall architecture design

, optional.python2.x or later when running a mapreduce task using Hadoop streaming, the Python runtime is required, optional.Infrastructure Layer:The infrastructure layer consists of 2 parts: The Zookeeper cluster and the Hadoop cluster. It provides infrastructure services for the underlying platform layer, such as naming services, Distributed file Systems, MapReduce, and so on.(1) The zookeeper cluster is used for named mappings as a named server for Hadoop clusters, and the Task Scheduler cons

Viewfilesystem of data merging scheme for HDFS cross-cluster

Preface In many cases, we will meet the needs of data fusion, such as the original a cluster, b cluster, later administrators think there are 2 sets of clusters, data access is not convenient, so try to merge a A, a cluster of a larger cluster, their data are placed on the same cluster. One way to do this is with Hadoop. DistCp tool to copy

A powerful tool for data exchange between HDFS and relational databases-a preliminary study of sqoop

HIVE_HOME =/home/hadoop/hive-0.8.1At this time, we can perform the test. We primarily use hive for interaction. Actually, we submit data from a relational database to hive and save it to HDFS for big data computing. Sqoop mainly includes the following commands or functions. Codegen Import a table definition into Hive

Block data balancer re-distribution in HDFs

When Hadoop 's HDFS cluster is used for a period of time, the disk usage of each DataNode node is definitely unbalanced, i.e. data skew at the data volume level,There are many ways to cause this:1. Add a new Datanode node2. human intervention reduces or increases the number of copies of dataWe all know that when the data

HDFS Data Encryption space-encryption Zone

Preface I have written many articles about data migration and introduced many tools and features related to HDFS, suchDistcp, viewfilesystemAnd so on. But the theme I want to talk about today has moved to another field.Data securityData security has always been a key concern for users. Therefore, data managers must follow the following principles: The

HDFS Meta Data management mechanism

1. Meta Data Management OverviewHDFs metadata, grouped by type, consists mainly of the following sections:1, the file, the directory of its own property information, such as file name, directory name, modify information and so on.2. Storing information about the information stored in the file, such as block information, block case, number of copies, etc.3, records the Datanode of HDFs information, for Datan

RDBMS data is timed to be captured to HDFs

Tags: Big data Sqoop HDFS RDBMS MySQL[TOC] RDBMS data timing acquisition to HDFS prefaceIn fact, it is not difficult to use sqoop timing from the MySQL import into HDFs, mainly the use of SQOOP commands and the operation of

Use flume to extract MySQL table data to HDFs in real time

Transferred from: http://blog.csdn.net/wzy0623/article/details/73650053First, why to use Flume in the past to build HAWQ Data Warehouse experimental environment, I use Sqoop extract from the MySQL database incrementally extract data to HDFs, and then use the HAWQ external table for access. This method requires only a small amount of configuration to complete the

Edge of hadoop source code: HDFS Data Communication Mechanism

It took some time to read the source code of HDFS. Yes.However, there have been a lot of parsing hadoop source code on the Internet, so we call it "edge material", that is, some scattered experiences and ideas. In short, HDFS is divided into three parts:Namenode maintains the distribution of data on datanode and is also responsible for some scheduling tasks;Data

Want to learn big data? This is a complete Big Data learning system.

Big Data The following are the big data learning ideas compiled by Alibaba Cloud. Stage 1: Linux This phase provides basic courses for Big Data learning, helping you get started with big

Dream Big Data, big data change life

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To work on big data-related high-wage jobs, first you need to sort out the big data industry distribution

systems, and development techniques. More detailed is related to: Data collection (where to collect data, if the tool is collected, cleaned, transformed, then integrated, and loaded into the data warehouse as the basis for analysis); Data access-related databases and storage architectures such as: cloud storage, Distr

HDFS Data Integrity

HDFS Data Integrity To ensure data integrity, data verification technology is generally used:1. Parity Technology2. md5, sha1, and other verification technologies3. Cyclic Redundancy verification technology of CRC-324. ECC memory error correction and Verification Technology HDFS

Problem resolution 1@HDFS actual data and backup data are inconsistent

Atorg.apache.hadoop.hbase.regionserver.HRegionServer.getRegionByEncodedName (hregionserver.java:2786) Atorg.apache.hadoop.hbase.regionserver.RSRpcServices.getRegion (rsrpcservices.java:922) Atorg.apache.hadoop.hbase.regionserver.RSRpcServices.getRegionInfo (rsrpcservices.java:1204) At Org.apache.hadoop.hbase.protobuf.generated.adminprotos$adminservice$2.callblockingmethod (AdminProtos.java : 20862) 4, solve the problem 3, the ZK on the/hbase directory deleted Zkcli.sh-server hkweb24:14601,hkweb

Linux boot Kettle and Linux and Windows kettle to HDFs write data (3)

Xshell run into the graphical interface in xmanager 1 sh spoon. SHCreate a new job1. write data into HDFs 1) kettle writes data to HDFs in LinuxDouble-click hadoop copy FilesRun this jobView data:1) kettle Write Data to

Old money says big Data (1)----Big data OLAP and OLTP analysis

: Architecture: Impala Technology is currently performing well, discarding the mapreduce design, combined with the HDFS cache can do better performance Maturity: more mature Efficiency: With parquet, performance is close to Hive+tez because it does not need to be started at a certain level of analysis faster than hive Learning curve: Learning SQL and Impala itself, so the difficulty is general. Summarize: Impala has

Data import and export between HDFS, Hive, MySQL, Sqoop (strongly recommended to see)

Tags: exporting. NET size Data Conversion ref DIR username Nat tmpHive Summary (vii) hive four ways to import data (strongly recommended to see) Several methods of data export of Hive https://www.iteblog.com/archives/955 (strongly recommended to see) Import MySQL data into HDFs

Flume use summary of data sent to Kafka, HDFs, Hive, HTTP, netcat, etc.

-ng agent-c conf-f conf/netcat.conf-n a1-dflume.root.logger=info,console. Then at another terminal, use Telnet to send data: command: Telnet hadoop-maser 44444[[emailprotected] ~]# telnet hadoop-master 44444Trying 192.168.194.6...Connected to Hadoop-master. Escape character is ' ^] '. Displaying the above information indicates that the connection flume succeeded, and then enter: 12213213213ok12321313ok will receive the corresponding message in flume:

Datax data synchronization between HDFs and MySQL

This case only applies to the data synchronization implementation between HDFs and MySQL.1, before compiling the installation note will release the following Setsharepath method in the path to your own installation path, the author of the/home/woody/datax/libs.2, RPM packaging, to modify the path in the *.spec file, Dataxpath, in addition, you may also need to comment out some of the assignment file code, s

DT Big Data Dream Factory free combat Big Data video complete sharing

InstituteHTTP://PAN.BAIDU.COM/S/1I30EWSD7,DT Big Data DreamWorks Spark, Scala, all videos of Hadoop, PPT and code links in Baidu Cloud network:Http://pan.baidu.com/share/home?uk=4013289088#category/type=0qq-pf-to=pcqq.groupLiaoliang Free 1000 collection of Big Data Spark, Hadoop, Scala, Docker videos released in 51CTO

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