Use Cases of hive concurrency Model
Concurrency support (http://issues.apache.org/jira/browse/HIVE-1293) is a must for databases and Their Use Cases are well understood. At least, we should try to support concurrent reading and writing. It is useful to add several locks that are currently locked. There is no direct requirement to add an API to explicitly obtain the lock. Therefore, all locks are obtained i
default database table is stored in the/user/hive/warehouse directory.(1) TextfileTextfile is the default format and is stored as a row store. Data is not compressed, disk overhead is large, data parsing cost is large.(2) SequencefileSequencefile is a binary file support provided by the Hadoop API, which is easy to use, can be segmented, and compressible. Sequencefile supports three types of compression options: NONE, RECORD, BLOCK. The record compre
Hive Installation (hadoop2.6.0 hive 1.2.1)Website address: http://hive.apache.org/downloads.html
three different modesInline mode: Metadata is kept in the inline derby mode, allowing only one session to connect to local standalone mode: Install MySQL locally, bar metadata in MySQL remote mode: Meta data placed in remote MySQL database
1. Embedded mode:
(1), modify/home/lin/hadoop/apache-
Hive Command Line interface
The command-line interface, the CLI, is the most common way to interact with hive. Using the CLI, users can create tables, check patterns, query tables, and so on. CLI Options
The following command shows a list of options provided by the CLI:
[Hadoop@localhost hive]$ hive--help--service CLI
Hive file Format1, TextfileDefault file formatData does not compress, disk overhead, data parsing overhead, can be combined with gzip, BZIP2 use (System Auto-detection, automatic decompression when executing queries)Data is not segmented by hive, so data cannot be manipulated in parallelTo create a command:2, Sequencefileis a binary file support provided by the Hadoop APIEasy to use, divisible, compressible
Transfer from http://superlxw1234.iteye.com/blog/1582880First, control the number of maps in the hive task:1. Typically, the job produces one or more map tasks through the directory of input.The main determinants are: The total number of input files, the file size of input, the size of the file block set by the cluster (currently 128M, can be set dfs.block.size in hive; command to see, this parameter can no
Here list common operations, more refer to https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL#LanguageManualDDL-Create%2FDrop%2FTruncateTable
Simple Table Creation
Create Table table_name (ID int, dtdontquery string, name string)
Create a partitioned table
Create Table table_name (ID int, dtdontquery string, name string) partitioned by (date string)
A table can have one or more partitions. Each partition exists in a
Hive in layman 's1. What is Hive1) What is hive?Here is an introduction to the Hive wiki:Hive is a data warehouse infrastructure built on top of Hadoop. IT provides tools to enable easy data ETL, a mechanism to put structures on the data, and the capability to querying and a Nalysis of large data sets stored in Hadoop files.
first, control the number of maps in the Hive task:1. Typically, the job produces one or more map tasks through the directory of input.The main determinants are: The total number of input files, the file size of input, the size of the file block set by the cluster (currently 128M, can be set dfs.block.size in hive; command to see, this parameter can not be customized modification);2. For example:A) Assuming
Conversion from http://blog.csdn.net/suine/article/details/5653137
1. Hive Introduction
Hive is an open-source hadoop-based data warehouse tool used to store and process massive structured data. It stores massive data in the hadoop file system instead of the database, but provides a data storage and processing mechanism for database-like databases, and uses hql (SQL-like) the language automatically manages
apache-hive-2.1.0 Installation
Installing Hive
Install the Namenode on Hadoop and copy the installation files to Linux/usr/hadoop/apache-hive-2.1.0-bin.tar.gz
Extract:
TAR–ZXVF apache-hive-2.1.0-bin.tar.gz
Add to environment variable
Vi/etc/profile
Edit
#hive
Export Hive_h
usage of Hive Beeline
Reprint: http://www.teckstory.com/hadoop-ecosystem/hive-new-cli-beeline-for-hive/
Hive is the Data Warehouse software of Hadoop ecosystem. It provides a mechanism to project structure onto large data sets stored in Hadoop. Hive allows to query this data
DML mainly operates on the data in the Hive table, but because of the characteristics of Hadoop, the performance of a single modification and deletion is very low, so it does not support the level operation;Mainly describes the most common methods of BULK INSERT data:1. Loading data from a fileSyntax: LOAD [LOCAL] ' filepath ' [OVERWRITE] into TABLE [PARTITION (Partcol1=val1, partcol2=val2 ...) ]Cases:Load ' /opt/data.txt ' into Table table1; --If t
Label:After the configuration of the Hive ODBC driver is successful, it becomes easier to access it through C #, which is divided into query and update operations, directly attached to the test code. The target platform for C # Engineering compilation needs to be noted in this process
Read-Write access code example: Public classhiveodbcclient {///
///
///
Public Statichiveodbcclient Current {Get{return Newhiveodbcclie
Tags: store rewritten cat POS Log monitor Web page infhttp://blog.csdn.net/wtq1993/article/details/52435563 http://blog.csdn.net/yeruby/article/details/51448188Hive on Spark vs. Sparksql vs Hive on TezThe previous article has been completed Sparksql,sparksql also has Thriftserver service, here say why also choose to engage in Hive-on-spark:
Sparksql-thriftserver all the results of all memory, fast
1. Hive IntroductionHive is an open-source hadoop-based data warehouse tool used to store and process massive structured data. It stores massive data in the hadoop file system instead of the database, but provides a data storage and processing mechanism for database-like databases, and uses HQL (SQL-like) the language automatically manages and processes the data. We can regard the volume of structured data in hive
1. Typically, the job produces one or more map tasks through the directory of input.The main determinants are: The total number of input files, the file size of input, the size of the file block set by the cluster (currently 128M, can be set dfs.block.size in hive; command to see, this parameter can not be customized modification);2. For example:A) Assuming that the input directory has 1 file A and a size of 780M, then Hadoop separates the file a into
Label: First, an overview of the task map: The process is to first delete the files on HDFs with Thdfsdelete, then import the data from the organization tables in Oracle into HDFS, establish hive connection-"Hive Build Table-" Tjava Get system Time-" Thiveload Import the files on HDFs into the hive table. The settings for each of these components are described b
Hive is a framework that occupies and plays an important role in the ecosystem architecture of Hadoop, and it is used in many practical businesses, so that the popularity of Hadoop is largely due to the presence of hive. So what exactly is hive and why it occupies such an important position in the Hadoop family, this article will focus on Hive's architecture (arc
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