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source/administration/production-notes.txt

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@@ -408,7 +408,7 @@ here:
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get some reporting back of its occurrence.
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#. Or, if you want to fail over manually, you can set your secondaries
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to ``priority:0`` in their configuration. Then manual action would be
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to ``priority:0`` in their configurations. Then manual action would be
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required for a failover. This is practical for a small cluster; for a
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large cluster you will want automation.
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source/core/aggregation.txt

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@@ -250,7 +250,7 @@ Pipeline Sequence Optimization
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.. versionchanged:: 2.4
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:term:`Aggregation` operations have an optimization phase which
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attempts to re-arrange the pipeline for improved performance.
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attempts to re-arrange the pipeline for improved performance.
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``$sort`` + ``$skip`` + ``$limit`` Sequence Optimization
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````````````````````````````````````````````````````````
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``$limit`` + ``$skip`` + ``$limit`` + ``$skip`` Sequence Optimization
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`````````````````````````````````````````````````````````````````````
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When you have continuous sequence of :pipeline:`$limit` pipeline
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When you have a continuous sequence of a :pipeline:`$limit` pipeline
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stage followed by a :pipeline:`$skip` pipeline stage, the
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aggregation will attempt to re-arrange the pipeline stages to combine
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the limits together and the skips together. For example, if the

source/core/replication.txt

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@@ -80,7 +80,7 @@ different usage patterns than the other members and require separation
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from normal traffic. Typically, hidden members provide reporting,
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dedicated backups, and dedicated read-only testing and integration
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support.
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To configure a member to be a hidden member, see
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:doc:`/tutorial/configure-a-hidden-replica-set-member`.
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one hour old, and the state of data for the member will reflect the state of the
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set an hour earlier.
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.. example:: If the current time is 09:52 and the secondary is a
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.. example:: If the current time is 09:52 and the secondary is
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delayed by an hour, no operation will be more recent than 08:52.
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Delayed members may help recover from various kinds of human error. Such
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documentation :doc:`/tutorial/configure-ssl` for more
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information. As with all MongoDB components, run arbiters on secure
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networks.
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To add an arbiter to the replica set, see
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:doc:`/tutorial/add-replica-set-arbiter`.
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replica set, there will be no rollback.
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Rollbacks remove those operations from the instance that were never
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replicated to the set so that the data set is in a consistent state.
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replicated to so that the data set is in a consistent state.
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The :program:`mongod` program writes rolled back data to a :term:`BSON`
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file that you can view using :program:`bsondump`, applied manually
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using :program:`mongorestore`.
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- If a significant portion of your workload entails in-place updates.
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In-place updates create a large number of operations but do not
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change the quantity data on disk.
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change the quantity of data on disk.
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If you can predict your replica set's workload to resemble one
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of the above patterns, then you may want to consider creating an oplog
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Without replication, a standalone MongoDB instance represents a single
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point of failure and any disruption of the MongoDB system will render
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the database unusable and potentially unrecoverable. Replication
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increase the reliability of the database instance, and replica sets
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increases the reliability of the database instance, and replica sets
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are capable of distributing reads to :term:`secondary` members depending
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on :term:`read preference`. For database work loads dominated by read
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operations, (i.e. "read heavy") replica sets can greatly increase the
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on all members of the replica set and on all :program:`mongos`
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instances that connect to the set.
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The key file must be less one kilobyte in size and may only contain
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The key file must be less than one kilobyte in size and may only contain
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characters in the base64 set. The key file must not have group or "world"
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permissions on UNIX systems. Use the following command to use the
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OpenSSL package to generate "random" content for use in a key file:

source/faq/fundamentals.txt

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:local:
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This document addresses basic high level questions about MongoDB and
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it's use.
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its use.
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If you don't find the answer you're looking for, check
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the :doc:`complete list of FAQs </faq>` or post your question to the

source/reference/command/compact.txt

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:dbcommand:`compact` compacts existing documents, but does not
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reset ``paddingFactor`` statistics for the collection. After the
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:dbcommand:`compact` MongoDB will use the existing
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:dbcommand:`compact` operation, MongoDB will use the existing
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``paddingFactor`` when allocating new records for documents in
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this collection.
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source/reference/command/replSetSyncFrom.txt

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behind the current member, :program:`mongod` will return and log a
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warning, but it still *will* replicate from the member that is behind.
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If you run :method:`rs.syncFrom()` during initial sync, MongoDB
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If you run :dbcommand:`replSetSyncFrom` during initial sync, MongoDB
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produces no error messages, but the sync target will not change
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until after the initial sync operation.
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source/reference/glossary.txt

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total data set. In production, all shards should be replica sets.
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See :term:`sharding`.
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.. seealso:: The documents in the :doc:`/sharding` section of manual.
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.. seealso:: The documents in the :doc:`/sharding` section of this manual.
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sharding
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A database architecture that enable horizontal scaling by splitting
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data into key ranges among two or more replica sets. This architecture
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is also known as "range-based partitioning." See :term:`shard`.
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.. seealso:: The documents in the :doc:`/sharding` section of manual.
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.. seealso:: The documents in the :doc:`/sharding` section of this manual.
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sharded cluster
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The set of nodes comprising a :term:`sharded <sharding>` MongoDB deployment. A sharded cluster
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consists of three config processes, one or more replica sets, and one or more
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:program:`mongos` routing processes.
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.. seealso:: The documents in the :doc:`/sharding` section of manual.
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.. seealso:: The documents in the :doc:`/sharding` section of this manual.
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partition
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A distributed system architecture that splits data into ranges.
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btree
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A data structure used by most database management systems
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for to store indexes. MongoDB uses b-trees for its indexes.
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to store indexes. MongoDB uses b-trees for its indexes.
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ISODate
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The international date format used by :program:`mongo`
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to display dates. E.g. ``YYYY-MM-DD HH:MM.SS.milis``.
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journal
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A sequential, binary transaction used to bring the database into
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A sequential, binary transaction log used to bring the database into
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a consistent state in the event of a hard shutdown. MongoDB
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enables journaling by default for 64-bit builds of MongoDB
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version 2.0 and newer. Journal files are pre-allocated and will
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exist as three 1GB file in the data directory. To make journal
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exist as three 1GB files in the data directory. To make journal
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files smaller, use :setting:`smallfiles`.
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When enabled, MongoDB writes data first to the journal and then
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haystack index
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In the context of :term:`geospatial` queries, haystack indexes
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enhance searches by creating "bucket" of objects grouped by a second
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enhance searches by creating "buckets" of objects grouped by a second
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criterion. For example, you might want all geospatial searches
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to first select along a non-geospatial dimension and then match
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on location. See :doc:`/core/geohaystack` for more
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shard key
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In a sharded collection, a shard key is the field that MongoDB
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uses to distribute documents among members of the
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uses to distribute documents among members of the
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:term:`sharded cluster`.
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hashed shard key
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A :ref:`hashed shard key <index-type-hashed>` is a special type
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of :term:`shard key` that uses a hash of the value in the shard
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key field is uses to distribute documents among members of the
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key field to distribute documents among members of the
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:term:`sharded cluster`.
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query
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.. seealso:: :ref:`Replica Set Failover <replica-set-failover>`.
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data-center awareness
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A property that allows clients to address members in a system to
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A property that allows clients to address members in a system
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based upon their location.
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:term:`Replica sets <replica set>` implement data-center
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``/etc/rc.d/`` directories.
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map-reduce
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A data and processing and aggregation paradigm consisting of a
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A data processing and aggregation paradigm consisting of a
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"map" phase that selects data, and a "reduce" phase that
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transforms the data. In MongoDB, you can run arbitrary aggregations
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over data using map-reduce.

source/tutorial/getting-started.txt

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Limit the Number of Documents in the Result Set
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To increase perfomance, you can constrain the size of the result by
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To increase performance, you can constrain the size of the result by
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limiting the amount of data your application must receive over the
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source/tutorial/shard-gridfs-data.txt

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db.runCommand( { shardCollection : "test.fs.chunks" , key : { files_id : 1 , n : 1 } } )
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You may also want to shard using just the ``file_id`` field, as in
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You may also want to shard using just the ``file_id`` field, as in
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the following operation:
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.. code-block:: javascript
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the values of ``files_id`` are always ascending, and applications
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will insert all new GridFS data to a single chunk and shard. If
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your write load is too high for a single server to handle, consider
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a different shard key or use a different value for different value
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a different shard key or use a different value
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for ``_id`` in the ``files`` collection.

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