- Elasticsearch Guide: other versions:
- Elasticsearch basics
- Quick starts
- Set up Elasticsearch
- Run Elasticsearch locally
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch configuration
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Miscellaneous cluster settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
- Field data cache settings
- Health Diagnostic settings
- Index lifecycle management settings
- Data stream lifecycle settings
- Index management settings
- Index recovery settings
- Indexing buffer settings
- License settings
- Local gateway settings
- Logging
- Machine learning settings
- Inference settings
- Monitoring settings
- Nodes
- Networking
- Node query cache settings
- Search settings
- Security settings
- Shard allocation, relocation, and recovery
- Shard request cache settings
- Snapshot and restore settings
- Transforms settings
- Thread pools
- Watcher settings
- Advanced configuration
- Important system configuration
- Bootstrap Checks
- Heap size check
- File descriptor check
- Memory lock check
- Maximum number of threads check
- Max file size check
- Maximum size virtual memory check
- Maximum map count check
- Client JVM check
- Use serial collector check
- System call filter check
- OnError and OnOutOfMemoryError checks
- Early-access check
- All permission check
- Discovery configuration check
- Bootstrap Checks for X-Pack
- Starting Elasticsearch
- Stopping Elasticsearch
- Discovery and cluster formation
- Add and remove nodes in your cluster
- Full-cluster restart and rolling restart
- Remote clusters
- Plugins
- Search your data
- Re-ranking
- Index modules
- Index templates
- Aliases
- Mapping
- Dynamic mapping
- Explicit mapping
- Runtime fields
- Field data types
- Aggregate metric
- Alias
- Arrays
- Binary
- Boolean
- Completion
- Date
- Date nanoseconds
- Dense vector
- Flattened
- Geopoint
- Geoshape
- Histogram
- IP
- Join
- Keyword
- Nested
- Numeric
- Object
- Pass-through object
- Percolator
- Point
- Range
- Rank feature
- Rank features
- Search-as-you-type
- Semantic text
- Shape
- Sparse vector
- Text
- Token count
- Unsigned long
- Version
- Metadata fields
- Mapping parameters
analyzer
coerce
copy_to
doc_values
dynamic
eager_global_ordinals
enabled
format
ignore_above
index.mapping.ignore_above
ignore_malformed
index
index_options
index_phrases
index_prefixes
meta
fields
normalizer
norms
null_value
position_increment_gap
properties
search_analyzer
similarity
store
subobjects
term_vector
- Mapping limit settings
- Removal of mapping types
- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
- Tokenizer reference
- Token filter reference
- Apostrophe
- ASCII folding
- CJK bigram
- CJK width
- Classic
- Common grams
- Conditional
- Decimal digit
- Delimited payload
- Dictionary decompounder
- Edge n-gram
- Elision
- Fingerprint
- Flatten graph
- Hunspell
- Hyphenation decompounder
- Keep types
- Keep words
- Keyword marker
- Keyword repeat
- KStem
- Length
- Limit token count
- Lowercase
- MinHash
- Multiplexer
- N-gram
- Normalization
- Pattern capture
- Pattern replace
- Phonetic
- Porter stem
- Predicate script
- Remove duplicates
- Reverse
- Shingle
- Snowball
- Stemmer
- Stemmer override
- Stop
- Synonym
- Synonym graph
- Trim
- Truncate
- Unique
- Uppercase
- Word delimiter
- Word delimiter graph
- Character filters reference
- Normalizers
- Ingest pipelines
- Example: Parse logs
- Enrich your data
- Processor reference
- Append
- Attachment
- Bytes
- Circle
- Community ID
- Convert
- CSV
- Date
- Date index name
- Dissect
- Dot expander
- Drop
- Enrich
- Fail
- Fingerprint
- Foreach
- Geo-grid
- GeoIP
- Grok
- Gsub
- HTML strip
- Inference
- IP Location
- Join
- JSON
- KV
- Lowercase
- Network direction
- Pipeline
- Redact
- Registered domain
- Remove
- Rename
- Reroute
- Script
- Set
- Set security user
- Sort
- Split
- Terminate
- Trim
- Uppercase
- URL decode
- URI parts
- User agent
- Ingest pipelines in Search
- Connectors
- Data streams
- Data management
- ILM: Manage the index lifecycle
- Tutorial: Customize built-in policies
- Tutorial: Automate rollover
- Index management in Kibana
- Overview
- Concepts
- Index lifecycle actions
- Configure a lifecycle policy
- Migrate index allocation filters to node roles
- Troubleshooting index lifecycle management errors
- Start and stop index lifecycle management
- Manage existing indices
- Skip rollover
- Restore a managed data stream or index
- Data tiers
- Roll up or transform your data
- Query DSL
- EQL
- ES|QL
- SQL
- Overview
- Getting Started with SQL
- Conventions and Terminology
- Security
- SQL REST API
- SQL Translate API
- SQL CLI
- SQL JDBC
- SQL ODBC
- SQL Client Applications
- SQL Language
- Functions and Operators
- Comparison Operators
- Logical Operators
- Math Operators
- Cast Operators
- LIKE and RLIKE Operators
- Aggregate Functions
- Grouping Functions
- Date/Time and Interval Functions and Operators
- Full-Text Search Functions
- Mathematical Functions
- String Functions
- Type Conversion Functions
- Geo Functions
- Conditional Functions And Expressions
- System Functions
- Reserved keywords
- SQL Limitations
- Scripting
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Categorize text
- Children
- Composite
- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Frequent item sets
- Geo-distance
- Geohash grid
- Geohex grid
- Geotile grid
- Global
- Histogram
- IP prefix
- IP range
- Missing
- Multi Terms
- Nested
- Parent
- Random sampler
- Range
- Rare terms
- Reverse nested
- Sampler
- Significant terms
- Significant text
- Terms
- Time series
- Variable width histogram
- Subtleties of bucketing range fields
- Metrics aggregations
- Pipeline aggregations
- Average bucket
- Bucket script
- Bucket count K-S test
- Bucket correlation
- Bucket selector
- Bucket sort
- Change point
- Cumulative cardinality
- Cumulative sum
- Derivative
- Extended stats bucket
- Inference bucket
- Max bucket
- Min bucket
- Moving function
- Moving percentiles
- Normalize
- Percentiles bucket
- Serial differencing
- Stats bucket
- Sum bucket
- Bucket aggregations
- Geospatial analysis
- Watcher
- Monitor a cluster
- Secure the Elastic Stack
- Elasticsearch security principles
- Start the Elastic Stack with security enabled automatically
- Manually configure security
- Updating node security certificates
- User authentication
- Built-in users
- Service accounts
- Internal users
- Token-based authentication services
- User profiles
- Realms
- Realm chains
- Security domains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- Kerberos authentication
- JWT authentication
- Integrating with other authentication systems
- Enabling anonymous access
- Looking up users without authentication
- Controlling the user cache
- Configuring SAML single-sign-on on the Elastic Stack
- Configuring single sign-on to the Elastic Stack using OpenID Connect
- User authorization
- Built-in roles
- Defining roles
- Role restriction
- Security privileges
- Document level security
- Field level security
- Granting privileges for data streams and aliases
- Mapping users and groups to roles
- Setting up field and document level security
- Submitting requests on behalf of other users
- Configuring authorization delegation
- Customizing roles and authorization
- Enable audit logging
- Restricting connections with IP filtering
- Securing clients and integrations
- Operator privileges
- Troubleshooting
- Some settings are not returned via the nodes settings API
- Authorization exceptions
- Users command fails due to extra arguments
- Users are frequently locked out of Active Directory
- Certificate verification fails for curl on Mac
- SSLHandshakeException causes connections to fail
- Common SSL/TLS exceptions
- Common Kerberos exceptions
- Common SAML issues
- Internal Server Error in Kibana
- Setup-passwords command fails due to connection failure
- Failures due to relocation of the configuration files
- Limitations
- Set up a cluster for high availability
- Optimizations
- Autoscaling
- Snapshot and restore
- REST APIs
- API conventions
- Common options
- REST API compatibility
- Autoscaling APIs
- Behavioral Analytics APIs
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- cat component templates
- cat count
- cat data frame analytics
- cat datafeeds
- cat fielddata
- cat health
- cat indices
- cat master
- cat nodeattrs
- cat nodes
- cat pending tasks
- cat plugins
- cat recovery
- cat repositories
- cat segments
- cat shards
- cat snapshots
- cat task management
- cat templates
- cat thread pool
- cat trained model
- cat transforms
- Cluster APIs
- Cluster allocation explain
- Cluster get settings
- Cluster health
- Health
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Prevalidate node removal
- Nodes reload secure settings
- Nodes stats
- Cluster Info
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Create or update desired nodes
- Get desired nodes
- Delete desired nodes
- Get desired balance
- Reset desired balance
- Cross-cluster replication APIs
- Connector APIs
- Create connector
- Delete connector
- Get connector
- List connectors
- Update connector API key id
- Update connector configuration
- Update connector index name
- Update connector features
- Update connector filtering
- Update connector name and description
- Update connector pipeline
- Update connector scheduling
- Update connector service type
- Create connector sync job
- Cancel connector sync job
- Delete connector sync job
- Get connector sync job
- List connector sync jobs
- Check in a connector
- Update connector error
- Update connector last sync stats
- Update connector status
- Check in connector sync job
- Claim connector sync job
- Set connector sync job error
- Set connector sync job stats
- Data stream APIs
- Document APIs
- Enrich APIs
- EQL APIs
- ES|QL APIs
- Features APIs
- Fleet APIs
- Graph explore API
- Index APIs
- Alias exists
- Aliases
- Analyze
- Analyze index disk usage
- Clear cache
- Clone index
- Close index
- Create index
- Create or update alias
- Create or update component template
- Create or update index template
- Create or update index template (legacy)
- Delete component template
- Delete dangling index
- Delete alias
- Delete index
- Delete index template
- Delete index template (legacy)
- Exists
- Field usage stats
- Flush
- Force merge
- Get alias
- Get component template
- Get field mapping
- Get index
- Get index settings
- Get index template
- Get index template (legacy)
- Get mapping
- Import dangling index
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists (legacy)
- List dangling indices
- Open index
- Refresh
- Resolve index
- Resolve cluster
- Rollover
- Shrink index
- Simulate index
- Simulate template
- Split index
- Unfreeze index
- Update index settings
- Update mapping
- Index lifecycle management APIs
- Create or update lifecycle policy
- Get policy
- Delete policy
- Move to step
- Remove policy
- Retry policy
- Get index lifecycle management status
- Explain lifecycle
- Start index lifecycle management
- Stop index lifecycle management
- Migrate indices, ILM policies, and legacy, composable and component templates to data tiers routing
- Inference APIs
- Delete inference API
- Get inference API
- Perform inference API
- Create inference API
- Stream inference API
- Update inference API
- AlibabaCloud AI Search inference service
- Amazon Bedrock inference service
- Anthropic inference service
- Azure AI studio inference service
- Azure OpenAI inference service
- Cohere inference service
- Elasticsearch inference service
- ELSER inference service
- Google AI Studio inference service
- Google Vertex AI inference service
- HuggingFace inference service
- Mistral inference service
- OpenAI inference service
- Watsonx inference service
- Info API
- Ingest APIs
- Licensing APIs
- Logstash APIs
- Machine learning APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create jobs
- Create calendars
- Create datafeeds
- Create filters
- Delete calendars
- Delete datafeeds
- Delete events from calendar
- Delete filters
- Delete forecasts
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Delete expired data
- Estimate model memory
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get model snapshots
- Get model snapshot upgrade statistics
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Reset jobs
- Revert model snapshots
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
- Update jobs
- Update model snapshots
- Upgrade model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Delete data frame analytics jobs
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Preview data frame analytics
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Update data frame analytics jobs
- Machine learning trained model APIs
- Clear trained model deployment cache
- Create or update trained model aliases
- Create part of a trained model
- Create trained models
- Create trained model vocabulary
- Delete trained model aliases
- Delete trained models
- Get trained models
- Get trained models stats
- Infer trained model
- Start trained model deployment
- Stop trained model deployment
- Update trained model deployment
- Migration APIs
- Node lifecycle APIs
- Query rules APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Root API
- Script APIs
- Search APIs
- Search Application APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Clear privileges cache
- Clear API key cache
- Clear service account token caches
- Create API keys
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Bulk create or update roles API
- Bulk delete roles API
- Create or update users
- Create service account tokens
- Delegate PKI authentication
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete service account token
- Delete users
- Disable users
- Enable users
- Enroll Kibana
- Enroll node
- Get API key information
- Get application privileges
- Get builtin privileges
- Get role mappings
- Get roles
- Query Role
- Get service accounts
- Get service account credentials
- Get Security settings
- Get token
- Get user privileges
- Get users
- Grant API keys
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect prepare authentication
- OpenID Connect authenticate
- OpenID Connect logout
- Query API key information
- Query User
- Update API key
- Update Security settings
- Bulk update API keys
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SAML complete logout
- SAML service provider metadata
- SSL certificate
- Activate user profile
- Disable user profile
- Enable user profile
- Get user profiles
- Suggest user profile
- Update user profile data
- Has privileges user profile
- Create Cross-Cluster API key
- Update Cross-Cluster API key
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Synonyms APIs
- Text structure APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Command line tools
- elasticsearch-certgen
- elasticsearch-certutil
- elasticsearch-create-enrollment-token
- elasticsearch-croneval
- elasticsearch-keystore
- elasticsearch-node
- elasticsearch-reconfigure-node
- elasticsearch-reset-password
- elasticsearch-saml-metadata
- elasticsearch-service-tokens
- elasticsearch-setup-passwords
- elasticsearch-shard
- elasticsearch-syskeygen
- elasticsearch-users
- Troubleshooting
- Fix common cluster issues
- Diagnose unassigned shards
- Add a missing tier to the system
- Allow Elasticsearch to allocate the data in the system
- Allow Elasticsearch to allocate the index
- Indices mix index allocation filters with data tiers node roles to move through data tiers
- Not enough nodes to allocate all shard replicas
- Total number of shards for an index on a single node exceeded
- Total number of shards per node has been reached
- Troubleshooting corruption
- Fix data nodes out of disk
- Fix master nodes out of disk
- Fix other role nodes out of disk
- Start index lifecycle management
- Start Snapshot Lifecycle Management
- Restore from snapshot
- Troubleshooting broken repositories
- Addressing repeated snapshot policy failures
- Troubleshooting an unstable cluster
- Troubleshooting discovery
- Troubleshooting monitoring
- Troubleshooting transforms
- Troubleshooting Watcher
- Troubleshooting searches
- Troubleshooting shards capacity health issues
- Troubleshooting an unbalanced cluster
- Capture diagnostics
- Upgrade Elasticsearch
- Migration guide
- What’s new in 8.16
- Release notes
- Elasticsearch version 8.16.2
- Elasticsearch version 8.16.1
- Elasticsearch version 8.16.0
- Elasticsearch version 8.15.5
- Elasticsearch version 8.15.4
- Elasticsearch version 8.15.3
- Elasticsearch version 8.15.2
- Elasticsearch version 8.15.1
- Elasticsearch version 8.15.0
- Elasticsearch version 8.14.3
- Elasticsearch version 8.14.2
- Elasticsearch version 8.14.1
- Elasticsearch version 8.14.0
- Elasticsearch version 8.13.4
- Elasticsearch version 8.13.3
- Elasticsearch version 8.13.2
- Elasticsearch version 8.13.1
- Elasticsearch version 8.13.0
- Elasticsearch version 8.12.2
- Elasticsearch version 8.12.1
- Elasticsearch version 8.12.0
- Elasticsearch version 8.11.4
- Elasticsearch version 8.11.3
- Elasticsearch version 8.11.2
- Elasticsearch version 8.11.1
- Elasticsearch version 8.11.0
- Elasticsearch version 8.10.4
- Elasticsearch version 8.10.3
- Elasticsearch version 8.10.2
- Elasticsearch version 8.10.1
- Elasticsearch version 8.10.0
- Elasticsearch version 8.9.2
- Elasticsearch version 8.9.1
- Elasticsearch version 8.9.0
- Elasticsearch version 8.8.2
- Elasticsearch version 8.8.1
- Elasticsearch version 8.8.0
- Elasticsearch version 8.7.1
- Elasticsearch version 8.7.0
- Elasticsearch version 8.6.2
- Elasticsearch version 8.6.1
- Elasticsearch version 8.6.0
- Elasticsearch version 8.5.3
- Elasticsearch version 8.5.2
- Elasticsearch version 8.5.1
- Elasticsearch version 8.5.0
- Elasticsearch version 8.4.3
- Elasticsearch version 8.4.2
- Elasticsearch version 8.4.1
- Elasticsearch version 8.4.0
- Elasticsearch version 8.3.3
- Elasticsearch version 8.3.2
- Elasticsearch version 8.3.1
- Elasticsearch version 8.3.0
- Elasticsearch version 8.2.3
- Elasticsearch version 8.2.2
- Elasticsearch version 8.2.1
- Elasticsearch version 8.2.0
- Elasticsearch version 8.1.3
- Elasticsearch version 8.1.2
- Elasticsearch version 8.1.1
- Elasticsearch version 8.1.0
- Elasticsearch version 8.0.1
- Elasticsearch version 8.0.0
- Elasticsearch version 8.0.0-rc2
- Elasticsearch version 8.0.0-rc1
- Elasticsearch version 8.0.0-beta1
- Elasticsearch version 8.0.0-alpha2
- Elasticsearch version 8.0.0-alpha1
- Dependencies and versions
Elastic GraphQL connector reference
editElastic GraphQL connector reference
editThe Elastic GraphQL connector is written in Python using the Elastic connector framework. View the source code for this connector.
Availability and prerequisites
editThis connector was introduced in Elastic 8.14.0, available as a self-managed self-managed connector.
To use this connector, satisfy all self-managed connector prerequisites. Importantly, you must deploy the connectors service on your own infrastructure. You have two deployment options:
- Run connectors service from source. Use this option if you’re comfortable working with Python and want to iterate quickly locally.
- Run connectors service in Docker. Use this option if you want to deploy the connectors to a server, or use a container orchestration platform.
This connector is in technical preview and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Technical preview features are not subject to the support SLA of official GA features.
Usage
editTo set up this connector in the UI, select the GraphQL tile when creating a new connector under Search → Connectors.
If you’re already familiar with how connectors work, you can also use the Connector APIs.
For additional operations, see Connectors UI in Kibana.
Deploy with Docker
editYou can deploy the GraphQL connector as a self-managed connector using Docker. Follow these instructions.
Step 1: Download sample configuration file
Download the sample configuration file. You can either download it manually or run the following command:
curl https://raw.githubusercontent.com/elastic/connectors/main/config.yml.example --output ~/connectors-config/config.yml
Remember to update the --output
argument value if your directory name is different, or you want to use a different config file name.
Step 2: Update the configuration file for your self-managed connector
Update the configuration file with the following settings to match your environment:
-
elasticsearch.host
-
elasticsearch.api_key
-
connectors
If you’re running the connector service against a Dockerized version of Elasticsearch and Kibana, your config file will look like this:
# When connecting to your cloud deployment you should edit the host value elasticsearch.host: http://host.docker.internal:9200 elasticsearch.api_key: <ELASTICSEARCH_API_KEY> connectors: - connector_id: <CONNECTOR_ID_FROM_KIBANA> service_type: graphql api_key: <CONNECTOR_API_KEY_FROM_KIBANA> # Optional. If not provided, the connector will use the elasticsearch.api_key instead
Using the elasticsearch.api_key
is the recommended authentication method. However, you can also use elasticsearch.username
and elasticsearch.password
to authenticate with your Elasticsearch instance.
Note: You can change other default configurations by simply uncommenting specific settings in the configuration file and modifying their values.
Step 3: Run the Docker image
Run the Docker image with the Connector Service using the following command:
docker run \ -v ~/connectors-config:/config \ --network "elastic" \ --tty \ --rm \ docker.elastic.co/integrations/elastic-connectors:8.16.2.0 \ /app/bin/elastic-ingest \ -c /config/config.yml
Refer to DOCKER.md
in the elastic/connectors
repo for more details.
Find all available Docker images in the official registry.
We also have a quickstart self-managed option using Docker Compose, so you can spin up all required services at once: Elasticsearch, Kibana, and the connectors service.
Refer to this README in the elastic/connectors
repo for more information.
Configuration
editConfigure GraphQL connector
editNote the following configuration fields:
-
http_endpoint
(required) -
Base URL of the GraphQL endpoint.
Example:
https://api.xyz.com/graphql
-
http_method
(required) -
GET
orPOST
. -
authentication_method
(required) -
Select from
No Auth
,Basic Auth
, andBearer Token
. -
username
- Required when using basic authentication.
-
password
- Required when using basic authentication.
-
token
- Required when using bearer token authentication.
-
graphql_query
(required) -
Query used to fetch data from the source. Can contain variables provided in the
graphql_variables
field. The connector will substitute the variables in the query with values fromgraphql_variables
and make a GraphQL query to the source.Example:
query getUser($id: ID!) { user(id: $id) { name email } }
-
graphql_variables
-
A JSON object of key/value pairs containing variables used in the GraphQL query. The connector will substitute the variables in the query with the values provided here and make a GraphQL query to the source.
Example:
For the GraphQL query
query getUser($id: ID!) { user(id: $id) { name } }
-
Where the value of
graphql_variables
is{"id": "123"}
-
The connector will execute
query getUser { user(id: "123") { name } }
to fetch data from the source
-
Where the value of
-
graphql_object_to_id_map
(required) -
A JSON mapping between GraphQL response objects to index and their ID fields. The connector will fetch data for each object (JSON key) and use the provided ID field (JSON value) to index the object into Elasticsearch. The connector will index all fields for each object specified in the mapping. Use dot
(.)
notation to specify the full path from the root of the GraphQL response to the desired object.Example:
The GraphQL query
query getUser { organization { users{ user_id name email} } }
fetches all available users from the source. To index every user as a separate document configure this field as below.{ "organization.users": "user_id" }
In this example
user_id
is unique in every user document. Therefore, we setuser_id
as the value fororganization.users
.The path provided in this field should only contain JSON objects and not lists.
-
headers
-
JSON object containing custom headers to be sent with each GraphQL request:
{ "content-type": "Application/json" }
-
pagination_model
(required) -
This field specifies the pagination model to be used by the connector. The connector supports
No pagination
andCursor-based pagination
pagination models.For cursor-based pagination, add
pageInfo {endCursor hasNextPage}
and anafter
argument variable in your query at the desired node (Pagination key
). Use theafter
query argument with a variable to iterate through pages. The default value for this field isNo pagination
. Example:For
Cursor-based pagination
, the query should look like this example:query getUsers($cursor: String!) { sampleData { users(after: $cursor) { pageInfo { endCursor hasNextPage } nodes { first_name last_name address } } } }
The value of
pagination_key
issampleData.users
so it must contain:-
pageInfo {endCursor hasNextPage}
-
the
after
argument with a variable when using cursor-based pagination
-
-
pagination_key
(required) -
Specifies which GraphQL object is used for pagination. Use
.
to provide the full path of the object from the root of the response.Example:
-
organization.users
-
-
connection_timeout
- Specifies the maximum time in seconds to wait for a response from the GraphQL source. Default value is 30 seconds.
Documents and syncs
editThe connector syncs the objects and entities based on GraphQL Query and GraphQL Object List.
Sync types
editFull syncs are supported by default for all connectors.
This connector currently does not support incremental syncs.
Sync rules
editBasic sync rules are identical for all connectors and are available by default.
Advanced Sync Rules
editAdvanced sync rules are not available for this connector in the present version.
Connector Client operations
editEnd-to-end Testing
editThe connector framework enables operators to run functional tests against a real data source, using Docker Compose. You don’t need a running Elasticsearch instance or GraphQL source to run this test.
Refer to Connector testing for more details.
To perform E2E testing for the GraphQL connector, run the following command:
$ make ftest NAME=graphql
For faster tests, add the DATA_SIZE=small
flag:
make ftest NAME=graphql DATA_SIZE=small
By default, DATA_SIZE=MEDIUM
.
Known issues
edit- Every document will be updated in every sync.
- If the same field name exists with different types across different objects, the connector might raise a mapping parser exception.
Refer to Known issues for a list of known issues for all connectors.
Troubleshooting
editSee Troubleshooting.
Security
editSee Security.
On this page