- Elasticsearch Guide: other versions:
- Getting Started
- Setup Elasticsearch
- Breaking changes
- Breaking changes in 5.0
- Search and Query DSL changes
- Mapping changes
- Percolator changes
- Suggester changes
- Index APIs changes
- Document API changes
- Settings changes
- Allocation changes
- HTTP changes
- REST API changes
- CAT API changes
- Java API changes
- Packaging
- Plugin changes
- Filesystem related changes
- Path to data on disk
- Aggregation changes
- Script related changes
- Breaking changes in 5.0
- API Conventions
- Document APIs
- Search APIs
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Cardinality Aggregation
- Extended Stats Aggregation
- Geo Bounds Aggregation
- Geo Centroid Aggregation
- Max Aggregation
- Min Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- Stats Aggregation
- Sum Aggregation
- Top hits Aggregation
- Value Count Aggregation
- Bucket Aggregations
- Children Aggregation
- Date Histogram Aggregation
- Date Range Aggregation
- Diversified Sampler Aggregation
- Filter Aggregation
- Filters Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- Global Aggregation
- Histogram Aggregation
- IP Range Aggregation
- Missing Aggregation
- Nested Aggregation
- Range Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
- Derivative Aggregation
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation
- Percentiles Bucket Aggregation
- Moving Average Aggregation
- Cumulative Sum Aggregation
- Bucket Script Aggregation
- Bucket Selector Aggregation
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Metrics Aggregations
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Shadow replica indices
- Indices Stats
- Indices Segments
- Indices Recovery
- Indices Shard Stores
- Clear Cache
- Flush
- Refresh
- Force Merge
- cat APIs
- Cluster APIs
- Query DSL
- Mapping
- Analysis
- Anatomy of an analyzer
- Testing analyzers
- 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
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Character Filters
- Modules
- Index Modules
- Ingest Node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- Lowercase Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- Dot Expander Processor
- How To
- Testing
- Glossary of terms
- Release Notes
- 5.0.2 Release Notes
- 5.0.1 Release Notes
- 5.0.0 Combined Release Notes
- 5.0.0 GA Release Notes
- 5.0.0-rc1 Release Notes
- 5.0.0-beta1 Release Notes
- 5.0.0-alpha5 Release Notes
- 5.0.0-alpha4 Release Notes
- 5.0.0-alpha3 Release Notes
- 5.0.0-alpha2 Release Notes
- 5.0.0-alpha1 Release Notes
- 5.0.0-alpha1 Release Notes (Changes previously released in 2.x)
WARNING: Version 5.0 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.
Install Elasticsearch with Docker
editInstall Elasticsearch with Docker
editElasticsearch is also available as a Docker image. The image is built with X-Pack.
Security note
editX-Pack is preinstalled in this image.
Please take a few minutes to familiarize yourself with X-Pack Security and how to change default passwords. The default password for the elastic
user is changeme
.
X-Pack includes a trial license for 30 days. After that, you can obtain one of the available subscriptions or disable Security. The Basic license is free and includes the Monitoring extension.
Obtaining Elasticsearch for Docker is as simple as issuing a docker pull
command against the Elastic Docker registry.
The Docker image can be retrieved with the following command:
docker pull docker.elastic.co/elasticsearch/elasticsearch:5.0.2
Running Elasticsearch from the command line
editDevelopment mode
editElasticsearch can be quickly started for development or testing use with the following command:
docker run -p 9200:9200 -e "http.host=0.0.0.0" -e "transport.host=127.0.0.1" docker.elastic.co/elasticsearch/elasticsearch:5.0.2
Production mode
editThe vm_max_map_count
kernel setting needs to be set to at least 262144
for production use.
Depending on your platform:
-
Linux
The
vm_map_max_count
setting should be set permanently in /etc/sysctl.conf:$ grep vm.max_map_count /etc/sysctl.conf vm.max_map_count=262144
To apply the setting on a live system type:
sysctl -w vm.max_map_count=262144
-
OSX with Docker for Mac
The
vm_max_map_count
setting must be set within the xhyve virtual machine:$ screen ~/Library/Containers/com.docker.docker/Data/com.docker.driver.amd64-linux/tty
Log in with root and no password. Then configure the
sysctl
setting as you would for Linux:sysctl -w vm.max_map_count=262144
-
OSX with Docker Toolbox
The
vm_max_map_count
setting must be set via docker-machine:docker-machine ssh sudo sysctl -w vm.max_map_count=262144
The following example brings up a cluster comprising two Elasticsearch nodes.
To bring up the cluster, use the docker-compose.yml
and just type:
docker-compose up
docker-compose
is not pre-installed with Docker on Linux.
Instructions for installing it can be found on the docker-compose webpage.
The node elasticsearch1
listens on localhost:9200
while elasticsearch2
talks to elasticsearch1
over a Docker network.
This example also uses Docker named volumes, called esdata1
and esdata2
which will be created if not already present.
version: '2' services: elasticsearch1: image: docker.elastic.co/elasticsearch/elasticsearch:5.0.2 container_name: elasticsearch1 environment: - cluster.name=docker-cluster - bootstrap.memory_lock=true - "ES_JAVA_OPTS=-Xms512m -Xmx512m" ulimits: memlock: soft: -1 hard: -1 nofile: soft: 65536 hard: 65536 mem_limit: 1g cap_add: - IPC_LOCK volumes: - esdata1:/usr/share/elasticsearch/data ports: - 9200:9200 networks: - esnet elasticsearch2: image: docker.elastic.co/elasticsearch/elasticsearch:5.0.2 environment: - cluster.name=docker-cluster - bootstrap.memory_lock=true - "ES_JAVA_OPTS=-Xms512m -Xmx512m" - "discovery.zen.ping.unicast.hosts=elasticsearch1" ulimits: memlock: soft: -1 hard: -1 nofile: soft: 65536 hard: 65536 mem_limit: 1g cap_add: - IPC_LOCK volumes: - esdata2:/usr/share/elasticsearch/data networks: - esnet volumes: esdata1: driver: local esdata2: driver: local networks: esnet: driver: bridge
To stop the cluster, type docker-compose down
. Data volumes will persist, so it’s possible to start the cluster again with the same data using docker-compose up
.
To destroy the cluster and the data volumes just type docker-compose down -v
.
Inspect status of cluster:
editcurl -u elastic http://127.0.0.1:9200/_cat/health Enter host password for user 'elastic': 1472225929 15:38:49 docker-cluster green 2 2 4 2 0 0 0 0 - 100.0%
Log messages go to the console and are handled by the configured Docker logging driver. By default you can access logs with docker logs
.
Configuring Elasticsearch with Docker
editElasticsearch loads its configuration from files under /usr/share/elasticsearch/config/
. These configuration files are documented in Configuring Elasticsearch and Setting JVM system properties.
The image offers several methods for configuring Elasticsearch settings with the conventional approach being to provide customized files, i.e. elasticsearch.yml
, but it’s also possible to use environment variables to set options:
A. Present the parameters via Docker environment variables
editFor example, to define the cluster name with docker run
you can pass -e "cluster.name=mynewclustername"
. Double quotes are required.
There is a difference between defining default settings and normal settings. The former are prefixed with default.
and cannot override normal settings, if defined.
B. Bind-mounted configuration
editCreate your custom config file and mount this over the image’s corresponding file.
For example, bind-mounting a custom_elasticsearch.yml
with docker run
can be accomplished with the parameter:
-v full_path_to/custom_elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml
The container runs Elasticsearch as user elasticsearch
using uid:gid 1000:1000
. Bind mounted host directories and files, such as custom_elasticsearch.yml
above, need to be accessible by this user. For the data and log dirs, such as /usr/share/elasticsearch/data
, write access is required as well.
C. Customized image
editIn some environments, it may make more sense to prepare a custom image containing your configuration. A Dockerfile
to achieve this may be as simple as:
FROM docker.elastic.co/elasticsearch/elasticsearch:5.0.2 ADD elasticsearch.yml /usr/share/elasticsearch/config/ USER root RUN chown elasticsearch:elasticsearch config/elasticsearch.yml USER elasticsearch
You could then build and try the image with something like:
docker build --tag=elasticsearch-custom . docker run -ti -v /usr/share/elasticsearch/data elasticsearch-custom
Notes for production use and defaults
editWe have collected a number of best practices for production use.
Any Docker parameters mentioned below assume the use of docker run
.
-
Elasticsearch inside the container runs as user
elasticsearch
using uid:gid1000:1000
. If you are bind mounting a local directory or file, ensure it is readable by this user while the data and log dirs additionally require write access. -
It is important to correctly set capabilities and ulimits via the Docker CLI. As seen earlier in the example docker-compose.yml, the following options are required:
--cap-add=IPC_LOCK --ulimit memlock=-1:-1 --ulimit nofile=65536:65536
-
Ensure
bootstrap.memory_lock
is set totrue
as explained in "Disable swapping".This can be achieved through any of the configuration methods, e.g. by setting the appropriate environments variable with
-e "bootstrap.memory_lock=true"
. -
The image exposes TCP ports 9200 and 9300. For clusters it is recommended to randomize the published ports with
--publish-all
, unless you are pinning one container per host. -
Use the
ES_JAVA_OPTS
environment variable to set heap size, e.g. to use 16GB use-e ES_JAVA_OPTS="-Xms16g -Xmx16g"
withdocker run
. It is also recommended to set a memory limit for the container. -
Pin your deployments to a specific version of the Elasticsearch Docker image, e.g.
docker.elastic.co/elasticsearch/elasticsearch:5.0.2
. -
Always use a volume bound on
/usr/share/elasticsearch/data
, as shown in the production example, for the following reasons:- The data of your elasticsearch node won’t be lost if the container is killed
- Elasticsearch is I/O sensitive and the Docker storage driver is not ideal for fast I/O
- It allows the use of advanced Docker volume plugins
-
If you are using the devicemapper storage driver (default on at least RedHat (rpm) based distributions) make sure you are not using the default
loop-lvm
mode. Configure docker-engine to use direct-lvm instead. - Consider centralizing your logs by using a different logging driver. Also note that the default json-file logging driver is not ideally suited for production use.
Next steps
editYou now have a test Elasticsearch environment set up. Before you start serious development or go into production with Elasticsearch, you will need to do some additional setup:
- Learn how to configure Elasticsearch.
- Configure important Elasticsearch settings.
- Configure important system settings.
On this page
- Security note
- Running Elasticsearch from the command line
- Development mode
- Production mode
- Inspect status of cluster:
- Configuring Elasticsearch with Docker
- A. Present the parameters via Docker environment variables
- B. Bind-mounted configuration
- C. Customized image
- D. Override the image’s default
- Notes for production use and defaults
- Next steps