Entwicklerinformationen
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| hadoop-bin | data-intensive clustering framework - tools | Mehr ... |
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. |
| hadoop-daemons-common | data-intensive clustering framework - common files | Mehr ... |
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. |
| hadoop-datanoded | data-intensive clustering framework - Data Node | Mehr ... |
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. |
| hadoop-jobtrackerd | data-intensive clustering framework - Job Tracker | Mehr ... |
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. |
| hadoop-namenoded | data-intensive clustering framework - Name Node | Mehr ... |
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. |
| hadoop-secondarynamenoded | data-intensive clustering framework - secondary Name Node | Mehr ... |
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. |
| hadoop-tasktrackerd | data-intensive clustering framework - Task Tracker | Mehr ... |
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. |
| libhadoop-index-java | data-intensive clustering framework - Lucene index support | Mehr ... |
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. |
| libhadoop-java | data-intensive clustering framework - Java libraries | Mehr ... |
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. |
| libhadoop-java-doc | data-intensive clustering framework - Java documentation | Mehr ... |
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. |
