hive patches

Overview As long as the correct file types and compression types (such as Textfile+gzip, sequencefile+snappy, etc.) are configured, hive can read and parse data as expected and provide SQL functionality. The structure of the sequencefile itself has been designed to compress content. So for the Sequencefile file compression, not the Sequencefile file, and then the file compression. Instead, the Content field is compressed when the Sequencefile file is

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

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

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-

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

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

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

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

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

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

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