elasticsearch/docs/reference/glossary.asciidoc

[glossary]
[[glossary]]
= Glossary of terms

[glossary]
[[glossary-analysis]] analysis ::

  Analysis is the process of converting <<glossary-text,full text>> to
  <<glossary-term,terms>>. Depending on which analyzer is used, these phrases:
  `FOO BAR`, `Foo-Bar`, `foo,bar` will probably all result in the
  terms `foo` and `bar`. These terms are what is actually stored in
  the index.
  +
  A full text query (not a <<glossary-term,term>> query) for `FoO:bAR` will
  also be analyzed to the terms `foo`,`bar` and will thus match the
  terms stored in the index.
  +
  It is this process of analysis (both at index time and at search time)
  that allows Elasticsearch to perform full text queries.
  +
  Also see <<glossary-text,text>> and <<glossary-term,term>>.

[[glossary-cluster]] cluster ::

  A cluster consists of one or more <<glossary-node,nodes>> which share the
  same cluster name. Each cluster has a single master node which is
  chosen automatically by the cluster and which can be replaced if the
  current master node fails.

[[glossary-document]] document ::

  A document is a JSON document which is stored in Elasticsearch. It is
  like a row in a table in a relational database. Each document is
  stored in an <<glossary-index,index>> and has a <<glossary-type,type>> and an
  <<glossary-id,id>>.
  +
  A document is a JSON object (also known in other languages as a hash /
  hashmap / associative array) which contains zero or more
  <<glossary-field,fields>>, or key-value pairs.
  +
  The original JSON document that is indexed will be stored in the
  <<glossary-source_field,`_source` field>>, which is returned by default when
  getting or searching for a document.

[[glossary-id]] id ::

  The ID of a <<glossary-document,document>> identifies a document. The
  `index/id` of a document must be unique. If no ID is provided,
  then it will be auto-generated. (also see <<glossary-routing,routing>>)

[[glossary-field]] field ::

  A <<glossary-document,document>> contains a list of fields, or key-value
  pairs. The value can be a simple (scalar) value (eg a string, integer,
  date), or a nested structure like an array or an object. A field is
  similar to a column in a table in a relational database.
  +
  The <<glossary-mapping,mapping>> for each field has a field _type_ (not to
  be confused with document <<glossary-type,type>>) which indicates the type
  of data that can be stored in that field, eg `integer`, `string`,
  `object`. The mapping also allows you to define (amongst other things)
  how the value for a field should be analyzed.

[[glossary-filter]] filter ::

  A filter is a non-scoring <<glossary-query,query>>, meaning that it does not score documents.
  It is only concerned about answering the question - "Does this document match?". 
  The answer is always a simple, binary yes or no. This kind of query is said to be made 
  in a <<query-filter-context,filter context>>, 
  hence it is called a filter. Filters are simple checks for set inclusion or exclusion. 
  In most cases, the goal of filtering is to reduce the number of documents that have to be examined.

[[glossary-index]] index ::

  An index is like a _table_ in a relational database. It has a
  <<glossary-mapping,mapping>> which contains a <<glossary-type,type>>,
  which contains the <<glossary-field,fields>> in the index.
  +
  An index is a logical namespace which maps to one or more
  <<glossary-primary-shard,primary shards>> and can have zero or more
  <<glossary-replica-shard,replica shards>>.

[[glossary-mapping]] mapping ::

  A mapping is like a _schema definition_ in a relational database. Each
  <<glossary-index,index>> has a mapping, which defines a <<glossary-type,type>>,
  plus a number of index-wide settings.
  +
  A mapping can either be defined explicitly, or it will be generated
  automatically when a document is indexed.

[[glossary-node]] node ::

  A node is a running instance of Elasticsearch which belongs to a
  <<glossary-cluster,cluster>>. Multiple nodes can be started on a single
  server for testing purposes, but usually you should have one node per
  server.
  +
  At startup, a node will use unicast to discover an existing cluster with
  the same cluster name and will try to join that cluster.

 [[glossary-primary-shard]] primary shard ::

  Each document is stored in a single primary <<glossary-shard,shard>>. When
  you index a document, it is indexed first on the primary shard, then
  on all <<glossary-replica-shard,replicas>> of the primary shard.
  +
  By default, an <<glossary-index,index>> has one primary shard. You can specify
  more primary shards to scale the number of <<glossary-document,documents>>
  that your index can handle.
  +
  You cannot change the number of primary shards in an index, once the index is
  index is created. However, an index can be split into a new index using the
  <<indices-split-index, split API>>.
  +
  See also <<glossary-routing,routing>>

[[glossary-query]] query ::

  A query is the basic component of a search. A search can be defined by one or more queries 
  which can be mixed and matched in endless combinations. While <<glossary-filter,filters>> are
  queries that only determine if a document matches, those queries that also calculate how well
  the document matches are known as "scoring queries". Those queries assign it a score, which is 
  later used to sort matched documents. Scoring queries take more resources than <<glossary-filter,non scoring queries>> 
  and their query results are not cacheable. As a general rule, use query clauses for full-text 
  search or for any condition that requires scoring, and use filters for everything else.

 [[glossary-replica-shard]] replica shard ::

  Each <<glossary-primary-shard,primary shard>> can have zero or more
  replicas. A replica is a copy of the primary shard, and has two
  purposes:
  +
  1.  increase failover: a replica shard can be promoted to a primary
  shard if the primary fails
  2.  increase performance: get and search requests can be handled by
  primary or replica shards.
  +
  By default, each primary shard has one replica, but the number of
  replicas can be changed dynamically on an existing index. A replica
  shard will never be started on the same node as its primary shard.

[[glossary-routing]] routing ::

  When you index a document, it is stored on a single
  <<glossary-primary-shard,primary shard>>. That shard is chosen by hashing
  the `routing` value. By default, the `routing` value is derived from
  the ID of the document or, if the document has a specified parent
  document, from the ID of the parent document (to ensure that child and
  parent documents are stored on the same shard).
  +
  This value can be overridden by specifying a `routing` value at index
  time, or a <<mapping-routing-field,routing
  field>> in the <<glossary-mapping,mapping>>.

[[glossary-shard]] shard ::

  A shard is a single Lucene instance. It is a low-level “worker” unit
  which is managed automatically by Elasticsearch. An index is a logical
  namespace which points to <<glossary-primary-shard,primary>> and
  <<glossary-replica-shard,replica>> shards.
  +
  Other than defining the number of primary and replica shards that an
  index should have, you never need to refer to shards directly.
  Instead, your code should deal only with an index.
  +
  Elasticsearch distributes shards amongst all <<glossary-node,nodes>> in the
  <<glossary-cluster,cluster>>, and can move shards automatically from one
  node to another in the case of node failure, or the addition of new
  nodes.

 [[glossary-source_field]] source field ::

  By default, the JSON document that you index will be stored in the
  `_source` field and will be returned by all get and search requests.
  This allows you access to the original object directly from search
  results, rather than requiring a second step to retrieve the object
  from an ID.

[[glossary-term]] term ::

  A term is an exact value that is indexed in Elasticsearch. The terms
  `foo`, `Foo`, `FOO` are NOT equivalent. Terms (i.e. exact values) can
  be searched for using _term_ queries.
  +
  See also <<glossary-text,text>> and <<glossary-analysis,analysis>>.

[[glossary-text]] text ::

  Text (or full text) is ordinary unstructured text, such as this
  paragraph. By default, text will be <<glossary-analysis,analyzed>> into
  <<glossary-term,terms>>, which is what is actually stored in the index.
  +
  Text <<glossary-field,fields>> need to be analyzed at index time in order to
  be searchable as full text, and keywords in full text queries must be
  analyzed at search time to produce (and search for) the same terms
  that were generated at index time.
  +
  See also <<glossary-term,term>> and <<glossary-analysis,analysis>>.

[[glossary-type]] type ::

  A type used to represent the _type_ of document, e.g. an `email`, a `user`, or a `tweet`.
  Types are deprecated and are in the process of being removed.  See <<removal-of-types>>.