This is the last call for comments for the review of debconf templates for hadoop.
The reviewed templates will be sent on Monday, April 12, 2010 to the package maintainer as a bug report and a mail will be sent to this list with "[BTS]" as a subject tag. --
Template: hadoop-namenoded/format Type: boolean Default: false _Description: Should namenoded's file system be formatted? The Name Node daemon manages the Hadoop Distributed File System (HDFS). Like a normal file system, it needs to be formatted prior to first use. If the HDFS file system is not formatted, the Name Node will fail to start. . This operation does not affect other file systems on this computer. You can safely choose to format the file system if you're using HDFS for the first time and don't have data from previous installations on this computer. . If you choose not to format the file system right now, you can do it later by executing "hadoop namenode -format" as the user "hadoop".
Source: hadoop Section: java Priority: optional Maintainer: Debian Java Maintainers <pkg-java-maintainers@lists.alioth.debian.org> Uploaders: Thomas Koch <thomas.k...@ymc.ch> Homepage: http://hadoop.apache.org Vcs-Browser: http://git.debian.org/?p=pkg-java/hadoop.git Vcs-Git: git://git.debian.org/pkg-java/hadoop.git Standards-Version: 3.8.4 Build-Depends: debhelper (>= 7.4.11), default-jdk, ant (>= 1.6.0), javahelper (>= 0.28), po-debconf, libcommons-cli-java, libcommons-codec-java, libcommons-el-java, libcommons-httpclient-java, libcommons-io-java, libcommons-logging-java, libcommons-net-java, libtomcat6-java, libjetty-java (>>6), libservlet2.5-java, liblog4j1.2-java, libslf4j-java, libxmlenc-java, liblucene2-java, libhsqldb-java, ant-optional, javacc Package: libhadoop-java Architecture: all Depends: ${misc:Depends}, libcommons-cli-java, libcommons-codec-java, libcommons-el-java, libcommons-httpclient-java, libcommons-io-java, libcommons-logging-java, libcommons-net-java, libtomcat6-java, libjetty-java (>>6), libservlet2.5-java, liblog4j1.2-java, libslf4j-java, libxmlenc-java Suggests: libhsqldb-java Description: data-intensive clustering framework - Java libraries Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . This package contains the core Java libraries. Package: libhadoop-index-java Architecture: all Depends: ${misc:Depends}, libhadoop-java (= ${binary:Version}), liblucene2-java Description: data-intensive clustering framework - Lucene index support Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . The org.apache.hadoop.contrib.index.main.UpdateIndex library provides support for managing an index using MapReduce. A distributed "index" is partitioned into "shards", each corresponding to a Lucene instance. This library's main() method uses a MapReduce job to analyze documents and update Lucene instances in parallel. Package: hadoop-bin Section: misc Architecture: all Depends: ${misc:Depends}, libhadoop-java (= ${binary:Version}), default-jre-headless | java6-runtime-headless Description: data-intensive clustering framework - tools Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . Hadoop implements MapReduce, using the Hadoop Distributed File System (HDFS). MapReduce divides applications into many small blocks of work. HDFS creates multiple replicas of data blocks for reliability, placing them on compute nodes around the cluster. MapReduce can then process the data where it is located. . This package provides the hadoop command line interface. See the hadoop-.*d packages for the Hadoop daemons. Package: hadoop-daemons-common Section: misc Architecture: all Depends: ${misc:Depends}, hadoop-bin (= ${binary:Version}), daemon, adduser, lsb-base (>= 3.2-14) Description: data-intensive clustering framework - common files Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . This package provides infrastructure for the Hadoop daemon packages, creating the hadoop user (with data and log directories) and maintaining the update-alternatives mechanism for hadoop configuration. Package: libhadoop-java-doc Section: doc Architecture: all Depends: ${misc:Depends}, libhadoop-java (= ${binary:Version}) Description: data-intensive clustering framework - Java documentation Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . This package provides the API documentation of Hadoop. Package: hadoop-tasktrackerd Section: misc Architecture: all Depends: ${misc:Depends}, hadoop-daemons-common (= ${binary:Version}) Description: data-intensive clustering framework - Task Tracker Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . The Task Tracker is the Hadoop service that accepts MapReduce tasks and computes results. Each node in a Hadoop cluster that should be doing computation should run a Task Tracker. Package: hadoop-jobtrackerd Section: misc Architecture: all Depends: ${misc:Depends}, hadoop-daemons-common (= ${binary:Version}) Description: data-intensive clustering framework - Job Tracker Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . The Job Tracker is a central service which is responsible for managing the Task Tracker services running on all nodes in an Hadoop Cluster. The Job Tracker allocates work to the Task Tracker nearest to the data with an available work slot. Package: hadoop-namenoded Section: misc Architecture: all Depends: ${misc:Depends}, hadoop-daemons-common (= ${binary:Version}) Description: data-intensive clustering framework - Name Node Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . The Hadoop Distributed File System (HDFS) requires one unique server, the Name Node, which manages the block locations of files on the file system. Package: hadoop-secondarynamenoded Section: misc Architecture: all Depends: ${misc:Depends}, hadoop-daemons-common (= ${binary:Version}) Description: data-intensive clustering framework - secondary Name Node Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . The secondary Name Node is responsible for checkpointing file system images. It is _not_ a failover partner for the name node, and may safely be run on the same machine. Package: hadoop-datanoded Section: misc Architecture: all Depends: ${misc:Depends}, hadoop-daemons-common (= ${binary:Version}) Description: data-intensive clustering framework - Data Node Hadoop is a software platform for writing and running applications that process vast amounts of data on a distributed file system. . Here's what makes Hadoop especially useful: * Scalable: Hadoop can reliably store and process petabytes. * Economical: It distributes the data and processing across clusters of commonly available computers. These clusters can number into the thousands of nodes. * Efficient: By distributing the data, Hadoop can process it in parallel on the nodes where the data is located. This makes it extremely rapid. * Reliable: Hadoop automatically maintains multiple copies of data and automatically redeploys computing tasks based on failures. . The Data Nodes in the Hadoop Cluster are responsible for serving up blocks of data over the network to Hadoop Distributed File System (HDFS) clients.
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