Enable Starburst Warp Speed for your cluster#

Starburst Warp Speed transparently adds an indexing and caching layer to enable higher performance. You can take advantage of the performance improvements by updating your cluster to suitable hardware and configuring the Starburst Warp Speed utility connector for any catalog accessing object storage with the Hive, Iceberg, or Delta Lake connector. A cluster deployment on Amazon Elastic Kubernetes Service (EKS), Microsoft Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE) is required.

Cluster management#

Starburst Warp Speed accommodates cluster expansion and contraction. Be aware of the following when scaling up or down:

  • When scaling a cluster horizontally (adding or removing worker nodes), Starburst Warp Speed continues operating, assuming that requirements are properly fulfilled. A cluster restart is not required when adding or removing nodes.

  • Scaling a cluster vertically to use larger nodes requires a cluster restart, which facilitates the replacement of all worker nodes to the larger node size.

  • After restarting the cluster, the default acceleration becomes active. New caches and indexes get created and populated based on the query workload. Any user-defined warmup rules are lost after restart, unless a database is configured for Starburst Warp Speed.

Default acceleration#

When a query accesses a column that is not accelerated, the system performs data and index materialization on the cluster to accelerate future access to the data in the column. This process of creating the indexes and caches is also called warmup. Warmup is performed individually by each worker based on the processed splits and uses the local high performance storage of the worker. Typically, these are SSD NVMe drives.

When new data is added to a table or the index and cache creation are in progress, the new portions of the table that are not accelerated are served from the object storage. After the asynchronous indexing and caching is complete, query processing accessing that data is accelerated, because the data is available directly in the cluster from the indexes and caches, and no longer has to be retrieved from the remote object storage.

This results in immediately improved performance for recently used datasets. In addition to the automatic default acceleration, advanced users can create specific warmup rules. The default acceleration has a lower priority than a user-created warmup rule.

Default acceleration is not performed for SELECT * FROM <table_name> queries that are commonly used to explore a table rather than to retrieve specific data.

Acceleration types#

Starburst Warp Speed uses different types of acceleration to improve query processing performance:

These acceleration types are used automatically by default acceleration, and can also be configured manually with warmup rules defined with the REST API.

Data cache acceleration#

Data cache acceleration is the system that caches the raw data objects from the object storage directly on the high-performance storage attached to the workers in the cluster. The data from one or more objects is processed in the cluster as splits. The data from the splits and associated metadata are managed as a row group. These row groups are used to accelerate any queries that access the contained data. The row groups are stored in a proprietary columnar block caching format.

Use the WARM_UP_TYPE_DATA value in the warmUpType property to configure data cache acceleration for a specific column with the REST API.

Index acceleration#

Index acceleration uses the data in a specific column in a table to create an index. This index is added to the row group and used when queries access a column to filter rows. It accelerates queries that use predicates, joins, filters, and searches, and minimizes data scanning.

The index types (such as bitmap, tree, and others), are determined automatically by the column data types, and data patterns and characteristics.

Use the WARM_UP_TYPE_BASIC value in the warmUpType property to configure index acceleration for a specific column with the REST API.

Text search acceleration#

Text search acceleration creates an index of the content of text columns using Apache Lucene. This index is used in query predicates. It accelerates queries that use predicates of filters and searches on text columns.

Starburst Warp Speed automatically enables text search acceleration, and maintains the indexes.

Text search acceleration uses Apache Lucene indexing to accelerate text analytics and provide fast text filters, particularly with LIKE predicates. The KeywordAnalyzer provides full support for LIKE semantics to search for the exact appearance of a value in a filtered column.

A use case is a search for a specific short string in a larger column, such as a description. For example, consider a table with a column named city and a value New York, United States. The index is case-sensitive. When indexing is applied to the column, the following query returns that record because the LIKE predicate is an exact match:

SELECT *
FROM tbl
WHERE city LIKE '%New York%'

The following queries do not return the results because the LIKE predicates are not an exact match. The first query is missing a space in the pattern:

SELECT *
FROM tbl
WHERE city LIKE '%NewYork%'

The second query uses lowercase:

SELECT *
FROM tbl
WHERE city LIKE '%new york%'

Text search acceleration indexing is recommended for:

  • Queries with LIKE predicates, prefix or suffix queries, or queries that use the starts_with functions.

  • Range queries on string columns. A common use is dates that are stored as strings that have range predicates. For example, date_string>='yyyy-mm-dd'.

Text search acceleration indexing supports the following data types:

  • CHAR

  • VARCHAR

  • CHAR ARRAY

  • VARCHAR ARRAY

Use the WARM_UP_TYPE_LUCENE value in the warmUpType property to configure text search acceleration for a specific column with the REST API.

Limitations:

  • The maximum supported string length is 33k characters.

  • Queries with nested expressions, such as starts_with(some_nested_method(col1), 'aaa'), are not accelerated.

Index and cache usage#

Once you have configured Starburst Warp Speed, you can view acceleration details and other summary statistics on the Index and cache usage tab in the Starburst Enterprise web UI.

For more information, see the reference documentation.

Automated clean up#

When the available storage on the cluster is about to run out of storage space, index and cache elements are automatically deleted. As a user or administrator, you don’t need to manage index and cache allocation. When the storage capacity threshold is exceeded, the system deletes the following content until the clean up threshold is reached:

  • All expired content based on the TTL value.

  • Content with the lowest values on the priority property that were created as a result of the default acceleration.

  • Content related to custom warmup rules for indexing and caching.

After a clean up, new data is indexed and cached as needed based on the data access by the processed queries.

Requirements#

To use Starburst Warp Speed, you need:

Supported object storage#

Starburst Warp Speed only supports the following object storage:

No other other object storage systems, including on-premises storage, S3-compatible storage such as MinIO, and any others are supported.

Cluster configuration#

Starburst Warp Speed requires your cluster to operate on a Kubernetes-based platform. Specifically the Plan your Kubernetes deployment apply.

In addition, Starburst Warp Speed requires specific nodes in terms of CPU and memory. The most important additional requirement is that sufficiently performant and sized Non-Volatile Memory Express (NVMe) solid-state drive (SSD) storage is available on all nodes, and exclusively used by SEP.

The following specific details apply for the supported platforms:

EKS

Required node sizes:

  • m7gd.4xlarge or larger

  • r7gd.4xlarge or larger

  • m6id.4xlarge or larger

  • m6idn.4xlarge or larger

  • m6gd.4xlarge or larger

  • r5d.4xlarge or larger

  • r5dn.4xlarge or larger

  • r6gd.4xlarge or larger

  • i3.4xlarge or larger

Create an EKS Managed Node Group with a specific size, and use it for all nodes in the cluster.

Include a bootstrap script when creating the node groups for creating an /opt/data directory to serve as a mount point for the SSD disks where the index and cache elements are stored. The value of localStorageMountPath in the values.yaml file is a subdirectory of the /opt/data mount point directory, as described in the All platforms section.

If you are using eksctl to create the cluster, you must embed the following script in the managedNodeGroups.preBootstrapCommands section:

preBootstrapCommands:
  "yum install -y mdadm"
  "sysctl -w fs.aio-max-nr=8388608 >> /etc/sysctl.conf"
  'devices=""; for device in $(ls /sys/block/); do if [[ $(grep -e "Amazon EC2 NVMe Instance Storage" -e "ec2-nvme-instance" /sys/block/${device}/device/subsysnqn -c 2> /dev/null) -gt 0 ]]; then devices="${devices} /dev/${device}"; fi; done; echo ${devices} > /tmp/devices'
  "mdadm --create /dev/md0 $(cat /tmp/devices) --level=0 --force --raid-devices=$(cat /tmp/devices | wc -w)"
  "mkfs.ext4 /dev/md0 -O ^has_journal"
  "mkdir -p /opt/data"
  "mount /dev/md0 /opt/data"
  "chmod 777 -R /opt/data"

If you do not have adequate privileges and are unable to use the bootstrap script, set the following configuration:

warpSpeed:
  image:
    tag: "a.b.c-awsprivileged"

AKS

Required node sizes:

  • Standard_L16s_v2 or larger Lsv2 series Azure VMs like Standard_L32s_v2 with SSDs attached. Lsv2-series VM SSDs are not encrypted by Azure Storage encryption. We strongly recommend Standard_L16s_v3 or larger Lsv3 series VMs.

  • In the Starburst Warp Speed section of values.yaml, set the following configuration:

warpSpeed:
  image:
    tag: "a.b.c-azure"

GKE

Required node sizes:

Attach the SSDs during node pool creation, and use the pool for the cluster creation.

Caution

Use the gcloud CLI, not Google Cloud console, for node pool creation. Using the Google console UI creates incompatible disk types.

Use the ephemeral-storage-local-ssd gcloud CLI command to provision local SSDs on the cluster. Select an even number of workers.

All platforms

Configuration considerations:

  • The task.max-worker-threads task property can not be changed with Starburst Warp Speed so it must be left at the default value.

  • SEP clusters with a vCPU count of 16 or fewer per worker node support a maximum of four Starburst Warp Speed catalogs. Clusters with larger worker nodes support a maximum of seven Starburst Warp Speed catalogs.

Warning

Starburst Warp Speed is not supported on a cluster running in Fault-tolerant execution mode.

Deployment and management is performed with the SEP Helm charts detailed in Deploy with Kubernetes and Configuring Starburst Enterprise in Kubernetes.

Add the following section in your values file for the specific cluster to enable Starburst Warp Speed:

warpSpeed:
  enabled: true

By default, it is disabled. The recommended memory allocation is automatically configured.

warpSpeed:
  enabled: true
  additionalHeapSizePercentage: 15

Starburst Warp Speed uses a filesystem on top of the underlying storage in order to not require privileged mode. Add the following filesystem and image configuration to your values file:

warpSpeed:
  enabled: false
    # Physical drive configuration requires the Warp Speed init container within
    # a worker pod to be privileged.
    # When configuration is done, the container's lifecycle ends.
    # If autoConfigure is not enabled, devices must be manually configured
    # before SEP pods are started. For example, during the node machine
    # bootstrap process (preBootstrapCommands script in EKS deployments).
    # This functionality is available for AKS, EKS, and GKE only.
    # For AWS, use default setting.
    # For Azure and GKE deployments, set autoConfigure to true.
  autoConfigure: false
    # Additional percentage of container memory reduced from heap size assigned to Java, must be less than 100
  additionalHeapSizePercentage: 15
  fileSystem:
    # The path for the mount point used to mount the local SSDs. Value differs
    # between clouds:
    # AWS, Azure - Defined by the user
    # GCP - Must be set to /mnt/stateful_partition/kube-ephemeral-ssd
    localStorageMountPath: /opt/data/<subdirectory>
  image:
    # Image that prepares the filesystem for Starburst Warp Speed.
    # Due to system limitations, this must be done by an init container running
    # in privileged mode.
    repository: "harbor.starburstdata.net/starburstdata/starburst-warpspeed-init"
    # Tag value differs between clouds:
    # AWS, GCP - Use default tag
    # Azure - Append the "azure" suffix, for example "1.0.0-azure"
    # Update this tag to the latest available version of the Starburst Warp
    # Speed init container
    tag: "1.0.10"
    pullPolicy: "IfNotPresent"

You need to ensure that you use a dedicated coordinator that is not scheduled for query processing, and adjust the query processing configuration to allow for more splits:

coordinator:
  additionalProperties: |
    ...
    node-scheduler.include-coordinator=false
    node-scheduler.max-splits-per-node=4096
    node-scheduler.max-unacknowledged-splits-per-task=2048
    node-scheduler.max-adjusted-pending-splits-per-task=2048

Use Helm to update the values and restart the cluster nodes. Confirm the cluster is operating correctly with the new configuration, but without any adjusted catalogs, and then proceed to configure catalogs.

Related to the catalog usage, the cluster needs to allow internal communication between all workers, as well as with the coordinator on all the HTTP ports configured by the different values for http-rest-port in all catalogs.

When starting the cluster, Starburst Warp Speed parses all configuration parameters and can send invalid warnings such as Configuration property 'cache-service.password' was not used. You can safely ignore these warnings.

Catalog configuration#

After a successful Cluster configuration, you can configure the desired catalogs to use Starburst Warp Speed.

Only catalogs using the Hive, Iceberg, or Delta Lake connectors can be accelerated:

  • connector.name=hive

  • connector.name=iceberg

  • connector.name=delta_lake

For more details, see Delta Lake considerations, Iceberg considerations, and Hive considerations.

Only catalogs backed by S3, GCS, and ADLS object storage are supported. For more details, see S3 considerations, GCS considerations, and ADLS considerations.

Update the example catalog that uses the Hive connector with AWS Glue in the values file.

catalogs:
  example: |
    connector.name=hive
    hive.metastore=glue
    ...

Enable Starburst Warp Speed on the catalog by updating the connector name to warp_speed and adding the required configuration properties:

catalogs:
  example: |
    connector.name=warp_speed
    warp-speed.proxied-connector=hive
    warp-speed.cluster-uuid=example-cluster-567891234567
    warp-speed.config.internal-communication.shared-secret=aLongSecretString
    hive.metastore=glue
    ...

The properties setting the connector name, the proxied connector and the cluster identifier are required.

The shared secret must be set to the same value as the secret for the cluster itself set in sharedSecret:. This is required unless the REST API is disabled.

For testing purposes, or alternatively for permanent usage of a new catalog name, such as faster, in parallel to the existing catalog, you can copy the configuration of a catalog and update it:

catalogs:
  example: |
    connector.name=hive
    hive.metastore=glue
    ...
  faster: |
    connector.name=warp_speed
    warp-speed.proxied-connector=hive
    warp-speed.cluster-uuid=example-cluster-567891234567
    warp-speed.config.internal-communication.shared-secret=aLongSecretString
    hive.metastore=glue
    ...

This allows you to query the same data with or without Starburst Warp Speed using different catalog names. However, existing scripts and statements that include the old catalog name example are not accelerated.

Catalog configuration properties#

The following table provides more information about the available catalog configuration properties:

Catalog configuration properties#

Property name

Description

connector.name

Required. Must be set to warp_speed.

warp-speed.proxied-connector

Required. The type of embedded connector that is used for accessing cold data through Starburst Warp Speed. Defaults to hive. Valid values are hive, iceberg, or delta-lake. All properties supported by these connectors, including metastore, file format, and connector properties, can be used to configure the catalog.

warp-speed.cluster-uuid

Required. Unique identifier of the cluster. Used as the folder name in the store path. Use the same value for all catalogs. When creating a new cluster and the same warp-speed.store.path and warp-speed.cluster-uuid are used, then the cluster warmup rules for index and cache creation are imported into the newly created cluster.

warp-speed.config.internal-communication.shared-secret

Required, unless REST API is disabled. The shared secret value of the cluster. It is configured for secure internal communication in sharedSecret: for the Kubernetes deployment. The identical value used for the property warp-speed.config.internal-communication.shared-secret for each catalog.

warp-speed.store.path

The optional path of the storage where metadata is managed. By default, this is managed in memory of the workers. You can use s3://, abfs://, or abfss:// as protocol for using remote object storage. Write access privileges are necessary. With remote a object storage configuration import-export and call-home data is also managed.

warp-speed.use-http-server-port

Specifies to run the REST API on the coordinator in the same server as SEP. Defaults to true. For details, see REST API access.

warp-speed.config.http-rest-port-enabled

Optional parameter to enable the REST API server on the coordinator and each worker for each catalog. Defaults to false. This REST API is only suitable for testing and debugging purposes, since it is not secured. For production, use the default configuration.

Set the property to true and add a unique http-rest-port value for each catalog. Endpoints use the specified port for a catalog, such as 8088, instead of the /ext/{catalogName} section of the context, and are otherwise identical to the secured REST API. Typically the port is not exposed outside the cluster, so users need to forward the port or call the API from inside the cluster.

Hive considerations#

Most configurations of the Hive connector are supported. Additionally, the following considerations apply when using the Hive connector as the proxied connector for Starburst Warp Speed:

For optimal performance, add the following properties to your catalog configuration:

catalogs:
  example: |
    ...
    hive.max-outstanding-splits-size=512MB
    hive.max-initial-splits=0
    hive.max-outstanding-splits=3000
    parquet.max-read-block-row-count=1024
    hive.dynamic-filtering.wait-timeout=1s
    ...

Iceberg considerations#

All configurations of the Iceberg connector are supported. Additionally, the following considerations apply when using the Iceberg connector as the proxied connector for Starburst Warp Speed:

  • Materialized views are supported.

  • Server-side encryption with S3 managed keys is supported. S3 client-side encryption is not supported.

  • An associated split is served from object storage and no acceleration occurs when:

For optimal performance, add the following properties to your catalog configuration:

catalogs:
  example: |
    ...
    parquet.max-read-block-row-count=1024
    iceberg.dynamic-filtering.wait-timeout=1s
    ...

Delta Lake considerations#

All configurations of the Delta Lake connector are supported. Additionally, the following considerations apply when using the Delta Lake connector as the proxied connector for Starburst Warp Speed:

  • Materialized views are not supported.

  • Server-side encryption with S3 managed keys is supported. S3 client-side encryption is not supported.

  • An associated split is served from object storage and no acceleration occurs when:

For optimal performance, add the following properties to your catalog configuration:

catalogs:
  example: |
    ...
    delta.max-initial-splits=0
    delta.max-outstanding-splits=3000
    parquet.max-read-block-row-count=1024
    delta.dynamic-filtering.wait-timeout=1s
    ...

S3 considerations#

Starburst Warp Speed supports Amazon S3 with catalogs using the Hive, Iceberg, and Delta Lake connectors.

Using the s3:// protocol is required.

GCS considerations#

Starburst Warp Speed supports Google Cloud Storage (GCS).

Authentication to GCS can use a JSON key file or an OAuth 2.0 access token configured identically for the Hive, Delta Lake, or Iceberg connector in the catalog properties:

hive.gcs.json-key-file-path=/path/to/gcs_keyfile.json
hive.gcs.use-access-token=false

View the Google Cloud Storage to learn more.

ADLS considerations#

Starburst Warp Speed supports Microsoft ADLS Gen 2. ADLS Gen1 is not supported.

Using the abfs:// or abfss:// protocol is required.

ADLS can be used with catalogs using the Hive and Delta Lake connectors with the following configuration properties to connect to Azure storage:

catalogs:
  faster: |
    ...
    warp-speed.store.path=abfs://<container_name@account_name>.dfs.core.windows.net/folder
    hive.azure.abfs-storage-account=<storage_account_name>
    hive.azure.abfs-access-key=xxx
    ...

It is possible to secure the connection with TLS and use the abfss protocol with the URI syntax.

Database configuration#

Advanced users, who configure custom warmup rules with the REST API, must use a database to prevent a loss of those rules with a restart of the cluster Operation without a database uses a temporary database.

The following RDBMS are supported:

  • MySQL

  • PostgreSQL

  • Oracle

Each catalog requires a separate database. You must create the database in an external server, and configure the JDBC connection string, including credentials, to the database. Refer to your RDBMS server and the documentation of the JDBC driver for details.

You can secure the connection to the database with username and password authentication:

warp-speed.jdbc.user=<database-user>
warp-speed.jdbc.password=<database-password>

  • database-user: Name of a user on the database with sufficient access to create tables and manage the data.

  • database-password: Password of the user.

You can use secrets to avoid exposing these sensitive values.

MySQL#

warp-speed.jdbc.connection.url=jdbc:mysql://<host>:<port>/<database>

  • host: The host name of the database server.

  • port: The HTTP port used by the database server. MySQL typically uses 3306.

  • database: The name of the database.

PostgreSQL#

warp-speed.jdbc.connection.url=jdbc:postgresql://<host>:<port>/<database>

  • host: The host name of the database server.

  • port: The HTTP port used by the database server. PostgreSQL typically uses 5432.

  • database: The name of the database schema.

Oracle#

warp-speed.jdbc.connection.url=jdbc:oracle:thin:@<host>:<port>/<schema-name>

  • host: The host name of the database server.

  • port: The HTTP port used by the database server. Oracle typically uses 1521.

  • database: The name of the database schema.

Starburst Warp Speed management#

Starburst Warp Speed automatically creates and manages its data based on processed queries, also called the Default acceleration

Additional custom configuration can be applied with the REST API. Persistent storage of this configuration requires a configured database.

The Index and cache usage tab provides summary statistics that indicate performance gains from using Starburst Warp Speed.

REST API access#

The Starburst Warp Speed REST API is available on the coordinator with a separate context for each catalog on the same port and domain as the SEP web UI, the Starburst Enterprise REST API and the Trino REST API.

Access to the REST API is controlled by the authentication and authorization identical to the Starburst Enterprise REST API.

The REST API is enabled by default, and can be disabled with warp-speed.use-http-server-port set to false. The shared secret value of the cluster, configured for secure internal communication, must be set in warp-speed.config.internal-communication.shared-secret for each catalog.

The endpoints path structure includes the name of the catalog, /ext/{catalogName}/{paths: .+}. The following example shows the /ext path to the warmup/warmup-rule-set endpoint for the catalog named faster on a cluster without authentication exposed via HTTP:

curl -X GET 'http://sep.example.com:8080/ext/faster/warmup/warmup-rule-get' \
  -H 'Accept: application/json'

A secured server needs to be accessed via HTTPS and potentially include authentication information:

curl -X GET 'https://sep.example.com/ext/faster/warmup/warmup-rule-get' \
  -H 'Accept: application/json'

REST API overview#

The following sections detail the REST API and available endpoints. The example calls use plain curl calls to the endpoints for the faster catalog on the cluster at sep.example.com using HTTPS and omitting any authentication.

Warming status#

You can determine the status of the warmup for Starburst Warp Speed with a GET operation of the /warming/status endpoint. It measures the warmup progress for splits across workers and if warming is currently taking place.

curl -X GET 'https://sep.example.com/ext/faster/warming/status' \
  -H 'Accept: application/json'

Example response:

{"nodesStatus":
  {"172.31.16.98": {"started":22136,"finished":22136},
   "172.31.25.207":{"started":20702,"finished":20702},
   "172.31.19.167":{"started":21116,"finished":21116},
   "172.31.22.28":{"started":20678,"finished":20678}},
   "warming":false}

The response shows that warmup started and finished on four workers, and is currently not in progress.

Debug tools#

The debug-tools endpoint requires an HTTP POST to specify the detailed command with a JSON payload to retrieve the desired data. You can use it to return the storage utilization:

curl -X POST "https://sep.example.com/ext/faster/debug-tools"  \
  -d '{"commandName" : "all","@class" : "io.trino.plugin.warp.execution.debugtools.DebugToolData"}' \
  -H 'Content-Type: application/json'

Example response:

{"coordinator-container":
  {"result":
    {"Storage_capacity":15000000,
     "Allocated 8k pages":1000000,
     "Num used stripes":0
    }
  }
}

Calculate the storage utilization percentage with (Allocated 8k pages / Storage_capacity) * 100.

Debug tools are blocked and can not be used during warming.

Row group count#

A row group in Starburst Warp Speed is a collection of index and cache elements that are used to accelerate processing of Trino splits from the SSD storage.

Note

A row group in Starburst Warp Speed is not equivalent to a Parquet row group or an ORC stripe, but a higher level artifact specific to Starburst Warp Speed. It can be related to a specific Parquet row group or ORC stripe but can also represent data from a whole file or more.

The row-group/row-group-count endpoint exposes all currently warmed up columns via an HTTP GET:

curl -X GET "https://sep.example.com/ext/faster/row-group/row-group-count" \
  -H "accept: application/json"

The result is a list of columns specified by schema.table.column.warumuptype as the key. The value represents the corresponding count of accelerated row groups. Warmup types:

In the following example, 20 row groups of the tripid column of the trips_data table in the trips schema are accelerated with a data cache and an index.

{
  trips.trips_data.tripid.WARM_UP_TYPE_DATA": 20,
  trips.trips_data.tripid.WARM_UP_TYPE_BASIC": 20
}

Create a warmup rule#

Use the warmup/warmup-rule-set endpoint with an HTTP POST and a JSON payload to create a warmup rule. You can create a warmup rule at the column or table level. Access to a table or column initiates the creation of index and caching data. Warmup rules can prevent index and cache creation or impact the order in which the index and cache data is removed, when storage limits are reached.

If there are warmup rules defined for both a column and its table, the column rule takes precedence, unless the priority of the column rule is lower than the priority of the table rule.

Column-level warmup rule#

The following example creates a column-level warmup rule for the int_1 column in the aaa table of the tmp schema:

curl -X POST 'https://sep.example.com/ext/faster/warmup/warmup-rule-set' \
  -d '[ { "column":{"classType":"RegularColumn", "key":"int_1"}, "schema": "tmp", "table": "aaa", "warmUpType": "WARM_UP_TYPE_BASIC", "priority": 8, "ttl": "PT720H", "predicates": [ ] } ]'
  -H 'Content-Type: application/json'

Find more details about the JSON payload in the table Warmup rule properties.

Table-level warmup rule#

The following example creates a table-level warmup rule for the aaa table of the tmp schema:

curl -X POST 'https://sep.example.com/ext/faster/warmup/warmup-rule-set' \
  -d '[ {"column":{"classType":"WildcardColumn","key":"*"},"schema": "tmp","table": "aaa","warmUpType": "WARM_UP_TYPE_BASIC","priority": -1,"ttl": "PT720H","predicates": [ ]} ]' \
  -H 'Content-Type: application/json'

Find more details about the JSON payload in the table Warmup rule properties.

Warmup rule properties#

Warmup rule properties#

Property name

Description

columnid

Name of the column to which a warmup rule is attached.

column

Defines the columns to accelerate in a table-level rule. Specify all columns by using classType set to WildcardColumn and key to * as used in Table-level warmup rule.

schema

Name of the schema that contains the specified table.

table

Name of the table that contains the specified column.

warmUpType

The materialization type performed on the specified column in the specified table. Valid values are WARM_UP_TYPE_DATA for data cache acceleration WARM_UP_TYPE_BASIC for index acceleration, and WARM_UP_TYPE_LUCENE for text search acceleration.

priority

Priority for the warmup rule. To ensure a column is accelerated even if storage capacity is exceeded, set the priority as high as 10. Rules with a higher priority take precedence. To ensure a column is never accelerated and prevent data cache or index creation, set to -10. Valid range of values: -10 to 10.

ttl

Duration for which the warmup rule remains active. Use PT0M to prevent expiration of the rule. Use duration specified in ISO-8601 duration format (PnDTnHnMn).

predicates

Defaults to all partitions. Use the JSON array syntax ["example1", "example2"] to limit to specific partitions.

Get all warmup rules#

The warmup/warmup-rule-get endpoint exposes all defined warmup rules via an HTTP GET:

curl -X GET 'https://sep.example.com/ext/faster/warmup/warmup-rule-get' \
  -H 'Accept: application/json'

Response:

{
  "id":186229827,
  "schema":"ride_sharing_dataset",
  "table":"trips_data_big",
  "columnid":"d_date",
  "column":
    {
      "classType":"RegularColumn",
      "key":"d_date"
     },
  "warmUpType":"WARM_UP_TYPE_BASIC",
  "priority":8.0,
  "ttl":2592000.000000000,
  "predicates":[]
}

Delete a warmup rule#

The warmup/warmup-rule-delete endpoint allows you to delete a warmup rule via an HTTP DELETE. The identifier for the rule is a required parameter and can be seen from the result of warmup/warmup-rule-get in the id value.

curl -X DELETE 'https://sep.example.com/ext/faster/warmup/warmup-rule-delete' \
  -d '[186229827]' -H 'Accept: application/json'

You can delete multiple rules by using a comma-separated list such as [186229827,186229827] as parameter.

When you delete a warmup rule, the column index and cache data is de-prioritized to data from a default acceleration, and therefore is subject to earlier deletion.

SQL support#

All SQL statements and functions supported by the connector used in the accelerated catalog are supported by Starburst Warp Speed:

Starburst Warp Speed supports all data types, including structural data types. All structural data types are accessible, but indexing is only applicable to fields within ROW data types.

For some functions, Starburst Warp Speed does not accelerate filtering operations on columns. For example, the following filtering operation is not accelerated:

SELECT count(*)
FROM catalog.schema.table
WHERE lower(company) = 'starburst';

Starburst Warp Speed indexing accelerates the following functions when used on the left or the right side of the predicate:

  • ceil(x) with REAL and DOUBLE data types

  • in_nan(x) with REAL and DOUBLE data types

  • cast(x as type) with DOUBLE cast to REAL, or any type cast to VARCHAR

  • cast(x as type) with DOUBLE and DECIMAL data types

  • day(d) and day_of_month(d) with DATE and TIMESTAMP data types

  • day_of_year(d) and doy(y) with DATE and TIMESTAMP data types

  • day_of_week(d) and dow(d) with DATE and TIMESTAMP data types

  • year(d) with DATE and TIMESTAMP data types

  • year_of_week(d) and yow(d) with DATE and TIMESTAMP data types

  • week(d) and week_of_year(d) with DATE and TIMESTAMP data types

  • LIKE and NOT LIKE with VARCHAR data type

  • contains(arr_varchar, value) with array of VARCHAR data type

  • substring and substr with VARCHAR data type

  • strpos with BIGINT data type

The maximum supported string length for any cached data type is 48000 characters.

FAQ#

What happens in case data is not cached and indexed? Am I getting partial results?

No. In case a split can be served from SSD, it is served; but if not, Starburst Warp Speed gets the data for this split from the object storage to complete the query and sends back the results. Then the index and cache are created asynchronously, based on priority and available SSD storage, so that future queries can leverage the index and cache.

Is there a chance a user can get stale results?

No. Starburst Warp Speed uses a mapping between the generated splits and index and cache data on SSDs during query processing. If a split can be served from SSD, it is; but if not, Starburst Warp Speed gets the data for this split from the object storage and then asynchronously indexes and caches it as appropriate.

What is the caching and indexing speed?

Performance depends on many different factors. For example, indexing and caching the entire TPC-DS SF1000 dataset takes about 20 minutes on a cluster with two workers with the machine size r5d.8xlarge.