- Elasticsearch Guide: other versions:
- Getting Started
- Setup
- Breaking changes
- API Conventions
- Document APIs
- Search APIs
- Search
- URI Search
- Request Body Search
- Search Template
- Search Shards API
- Aggregations
- Min Aggregation
- Max Aggregation
- Sum Aggregation
- Avg Aggregation
- Stats Aggregation
- Extended Stats Aggregation
- Value Count Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Cardinality Aggregation
- Geo Bounds Aggregation
- Top hits Aggregation
- Scripted Metric Aggregation
- Global Aggregation
- Filter Aggregation
- Filters Aggregation
- Missing Aggregation
- Nested Aggregation
- Reverse nested Aggregation
- Children Aggregation
- Terms Aggregation
- Significant Terms Aggregation
- Range Aggregation
- Date Range Aggregation
- IPv4 Range Aggregation
- Histogram Aggregation
- Date Histogram Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- Facets
- Suggesters
- Multi Search API
- Count API
- Search Exists API
- Validate API
- Explain API
- Percolator
- More Like This API
- Field stats API
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Delete Mapping
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Warmers
- Status
- Indices Stats
- Indices Segments
- Indices Recovery
- Clear Cache
- Flush
- Refresh
- Optimize
- Shadow replica indices
- Upgrade
- cat APIs
- Cluster APIs
- Query DSL
- Queries
- Match Query
- Multi Match Query
- Bool Query
- Boosting Query
- Common Terms Query
- Constant Score Query
- Dis Max Query
- Filtered Query
- Fuzzy Like This Query
- Fuzzy Like This Field Query
- Function Score Query
- Fuzzy Query
- GeoShape Query
- Has Child Query
- Has Parent Query
- Ids Query
- Indices Query
- Match All Query
- More Like This Query
- Nested Query
- Prefix Query
- Query String Query
- Simple Query String Query
- Range Query
- Regexp Query
- Span First Query
- Span Multi Term Query
- Span Near Query
- Span Not Query
- Span Or Query
- Span Term Query
- Term Query
- Terms Query
- Top Children Query
- Wildcard Query
- Minimum Should Match
- Multi Term Query Rewrite
- Template Query
- Filters
- And Filter
- Bool Filter
- Exists Filter
- Geo Bounding Box Filter
- Geo Distance Filter
- Geo Distance Range Filter
- Geo Polygon Filter
- GeoShape Filter
- Geohash Cell Filter
- Has Child Filter
- Has Parent Filter
- Ids Filter
- Indices Filter
- Limit Filter
- Match All Filter
- Missing Filter
- Nested Filter
- Not Filter
- Or Filter
- Prefix Filter
- Query Filter
- Range Filter
- Regexp Filter
- Script Filter
- Term Filter
- Terms Filter
- Type Filter
- Queries
- Mapping
- Analysis
- Analyzers
- Tokenizers
- Token Filters
- Standard Token Filter
- ASCII Folding Token Filter
- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
- Shingle Token Filter
- Stop Token Filter
- Word Delimiter Token Filter
- Stemmer Token Filter
- Stemmer Override Token Filter
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Snowball Token Filter
- Phonetic Token Filter
- Synonym Token Filter
- Compound Word Token Filter
- Reverse Token Filter
- Elision Token Filter
- Truncate Token Filter
- Unique Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Trim Token Filter
- Limit Token Count Token Filter
- Hunspell Token Filter
- Common Grams Token Filter
- Normalization Token Filter
- CJK Width Token Filter
- CJK Bigram Token Filter
- Delimited Payload Token Filter
- Keep Words Token Filter
- Keep Types Token Filter
- Classic Token Filter
- Apostrophe Token Filter
- Character Filters
- ICU Analysis Plugin
- Modules
- Index Modules
- Testing
- Glossary of terms
WARNING: Version 1.7 of Elasticsearch has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
Installation
editInstallation
editElasticsearch requires at least Java 7. Specifically as of this writing, it is recommended that you use the Oracle JDK version 1.8.0_25. Java installation varies from platform to platform so we won’t go into those details here. Oracle’s recommended installation documentation can be found on Oracle’s website. Suffice to say, before you install Elasticsearch, please check your Java version first by running (and then install/upgrade accordingly if needed):
java -version echo $JAVA_HOME
Once we have Java set up, we can then download and run Elasticsearch. The binaries are available from www.elastic.co/downloads
along with all the releases that have been made in the past. For each release, you have a choice among a zip
or tar
archive, or a DEB
or RPM
package. For simplicity, let’s use the tar file.
Let’s download the Elasticsearch 1.7.6 tar as follows (Windows users should download the zip package):
curl -L -O https://download.elastic.co/elasticsearch/elasticsearch/elasticsearch-1.7.6.tar.gz
Then extract it as follows (Windows users should unzip the zip package):
tar -xvf elasticsearch-1.7.6.tar.gz
It will then create a bunch of files and folders in your current directory. We then go into the bin directory as follows:
cd elasticsearch-1.7.6/bin
And now we are ready to start our node and single cluster (Windows users should run the elasticsearch.bat file):
./elasticsearch
If everything goes well, you should see a bunch of messages that look like below:
./elasticsearch [2014-03-13 13:42:17,218][INFO ][node ] [New Goblin] version[1.7.6], pid[2085], build[5c03844/2014-02-25T15:52:53Z] [2014-03-13 13:42:17,219][INFO ][node ] [New Goblin] initializing ... [2014-03-13 13:42:17,223][INFO ][plugins ] [New Goblin] loaded [], sites [] [2014-03-13 13:42:19,831][INFO ][node ] [New Goblin] initialized [2014-03-13 13:42:19,832][INFO ][node ] [New Goblin] starting ... [2014-03-13 13:42:19,958][INFO ][transport ] [New Goblin] bound_address {inet[/0:0:0:0:0:0:0:0:9300]}, publish_address {inet[/192.168.8.112:9300]} [2014-03-13 13:42:23,030][INFO ][cluster.service] [New Goblin] new_master [New Goblin][rWMtGj3dQouz2r6ZFL9v4g][mwubuntu1][inet[/192.168.8.112:9300]], reason: zen-disco-join (elected_as_master) [2014-03-13 13:42:23,100][INFO ][discovery ] [New Goblin] elasticsearch/rWMtGj3dQouz2r6ZFL9v4g [2014-03-13 13:42:23,125][INFO ][http ] [New Goblin] bound_address {inet[/0:0:0:0:0:0:0:0:9200]}, publish_address {inet[/192.168.8.112:9200]} [2014-03-13 13:42:23,629][INFO ][gateway ] [New Goblin] recovered [1] indices into cluster_state [2014-03-13 13:42:23,630][INFO ][node ] [New Goblin] started
Without going too much into detail, we can see that our node named "New Goblin" (which will be a different Marvel character in your case) has started and elected itself as a master in a single cluster. Don’t worry yet at the moment what master means. The main thing that is important here is that we have started one node within one cluster.
As mentioned previously, we can override either the cluster or node name. This can be done from the command line when starting Elasticsearch as follows:
./elasticsearch --cluster.name my_cluster_name --node.name my_node_name
Also note the line marked http with information about the HTTP address (192.168.8.112
) and port (9200
) that our node is reachable from. By default, Elasticsearch uses port 9200
to provide access to its REST API. This port is configurable if necessary.