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.
Warning
Support for HDFS is not enabled by default,
but can be activated by setting the fs.hadoop.enabled
property to true
in
your catalog configuration file. See also,
Supported object storage.
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.
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 performed for SELECT * FROM <table_name>
queries
that are commonly used to explore a table rather than to retrieve specific data.
The maximum number of accelerated columns in SELECT *
clauses is dynamic and
depends on the column type.
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.Query predicates can contain a maximum of 128 unique columns.
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.
Index and cache resiliency #
Note
Index and cache resiliency is a public preview feature. Contact Starburst support with questions or feedback.
Starburst Warp Speed optionally provides index and cache resiliency. When a new index is created or data is cached, it is stored on the SSD NVMe (nonvolatile memory express) drives attached to each worker by default, and in addition on a dedicated, shared bucket in your object storage. When you scale the cluster, the indexes and data cache remain available in the shared storage.
The resiliency feature enables fast warmup when scaling up by adding worker nodes to a cluster. This also eliminates the need for keeping instances idling when a cluster is not in use. Instead, when a cluster needs to warm an index or data cache, it first accesses the designated bucket on the object storage to check if the indexes or cache are ready and loads them accordingly. If the indexes or cache are not available in the shared object storage or cannot be loaded for any reason, the data is warmed as usual.
There are three storage tiers accessed for queries:
Hot data and index: Uses SSD NVMe attached to the workers in a cluster to process queries and store hot data and a cache for optimal performance. This layer is enabled by default with Starburst Warp Speed.
Warm data and index: Indexes and cached data are stored in a designated object storage bucket. This layer is shared amongst all of your workers to ensure minimal resources are allocated to indexing when scaling up a cluster and adds resiliency. When a cluster is scaled down or eliminated, and nodes are shut down, the indexes remain available as warm data. The warm layer is disabled by default. Enabling index and cache resiliency makes the warm tier available for fast warmup of indexes and caches.
Cold data: Direct access of your object storage.
With this tiered approach, you can continue using your existing scaling and auto-scaling policies.
To use Starburst Warp Speed index and cache resiliency, you must include read/write permissions to a backup location in object storage. The following shows a privilege example for read/write access to S3:
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "s3ReadWrite",
"Effect": "Allow",
"Action": [
"s3:ListBucket",
"s3:GetBucketPolicy",
"s3:GetObject",
"s3:GetObjectAttributes",
"s3:PutObject",
"s3:DeleteObject",
"s3:AbortMultipartUpload"
],
"Resource": [
"arn:aws:s3:::<backup-location-bucket>/*",
"arn:aws:s3:::<backup-location-bucket>",
"arn:aws:s3:::<data-bucket>/*",
"arn:aws:s3:::<data-bucket>/*"
]
},
{
"Sid": "VisualEditor1",
"Effect": "Allow",
"Action": [
"s3:ListAllMyBuckets",
"glue:*"
],
"Resource": "*"
}
]
}
Storing the indexes and data caches can fill up your object storage. Setting a lifecycle policy to control the associated cost is highly recommended. Refer to the following lifecycle documentation for your cloud provider:
As a best practice, allocate at least the average available SSD storage of your cluster.
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:
One or more catalogs that use the Hive, Iceberg, or Delta Lake connectors.
A cluster deployment on Amazon Elastic Kubernetes Service (EKS), Microsoft Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE) as detailed in Cluster configuration.
A valid Starburst Enterprise license.
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.
Note
Starburst strongly recommends using a native file system implementation rather than the default Hadoop file system implementation for any catalogs with Starburst Warp Speed.
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 largerr7gd.4xlarge
or largerm6id.4xlarge
or largerm6idn.4xlarge
or largerm6gd.4xlarge
or largerr5d.4xlarge
or largerr5dn.4xlarge
or largerr6gd.4xlarge
or largeri3.4xlarge
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"
SEP supports AWS Bottlerocket nodes for EKS workloads. This includes support for Starburst Warp Speed configurations. To deploy SEP using Bottlerocket nodes, add the following to your Amazon EC2 user data:
[settings.bootstrap-containers.disk-setup]
essential = true
mode = "once"
source = "http://harbor.starburstdata.net/starburstdata/starburst-warpspeed-init:1.0.17-bottlerocket"
AKS
Required node sizes:
Standard_L16s_v2
or largerLsv2
series Azure VMs likeStandard_L32s_v2
with SSDs attached. Lsv2-series VM SSDs are not encrypted by Azure Storage encryption. We strongly recommendStandard_L16s_v3
or largerLsv3
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:
n2-highmem-16
or larger with a minimum of two local NVME SSDs attachedn2d-standard-16
or largerGKE version
1.25.3-gke.1800
or higher
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
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, or S3 deployments using the native
# filesystem implementation, set autoConfigure to true.
autoConfigure: true
# 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/data
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: "1.0.16"
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
# Do not configure the following property if you are using a native
# filesystem implementation.
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
# Do not configure the following property if you are using a native
# filesystem implementation.
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:
Property name |
Description |
---|---|
|
Required. Must be set to |
|
Required. The type of embedded connector that is used for accessing cold
data through Starburst Warp Speed. Defaults to |
|
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 |
|
Required, unless REST API is disabled or you are using a native filesystem
implementation The shared secret value of the cluster. It is configured
for secure internal communication
in |
|
The path to a bucket in object storage where SSD data is backed up for fast
cache rehydration. Requires |
|
Enable or disable index and cache resiliency. Defaults to |
|
Specifies to run the REST API on the coordinator in the same server as
SEP. Defaults to |
|
Optional parameter to enable the REST API server on the coordinator and
each worker for each catalog. Defaults to Set the property to Do not configure if you are using a native filesystem implementation. |
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:
Table redirection from a catalog using the Hive connector to Delta Lake or Iceberg is not supported.
Materialized views are supported.
S3 proxy is not supported.
Server-side encryption with S3 managed keys and KMS managed keys is supported. S3 client-side encryption is not supported.
ORC ACID transactional tables are not supported.
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:
A row-level update or delete operation.
A merge operation that causes a record update.
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:
A row-level update or delete operation.
A merge operation that causes a record update.
For optimal performance, add the following properties to your catalog configuration:
catalogs:
example: |
...
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 Legacy Google Cloud Storage support to learn more.
The following OAuth 2.0 access scopes for Google APIs must be attached during GKE node creation to enable the index and cache resiliency:
For more information about authorization, refer to Google Cloud Service accounts documentation.
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.
Warmup rule persistency#
Advanced users, who configure custom warmup rules with the REST API, must use object storage to ensure user-defined warmup rules are not lost after a cluster restart.
Specify an object store path where custom warmup rules are stored. This path should point to a location in your object storage bucket:
warp-speed.objectstore.store.path=protocol://account_name.path.to.bucket/storage
Specify a separate path for each catalog. Multiple catalogs can use a single object storage bucket with a separate file for each catalog.
Storing custom warmup rules can fill up your object storage. Set a lifecycle configuration to manage warmup rules stored in your bucket and exclude them from deletion. Refer to the following lifecycle documentation for your cloud provider:
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.
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.
Note
If you are using a native file system implementation
rather than the default Hadoop implementation, do not add
warp-speed.use-http-server-port
or
warp-speed.config.internal-communication.shared-secret
to your configuration.
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:
WARM_UP_TYPE_DATA
represents data cache acceleration.WARM_UP_TYPE_BASIC
represents index acceleration.WARM_UP_TYPE_LUCENE
represents text search acceleration.
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#
Property name |
Description |
---|---|
|
Name of the column to which a warmup rule is attached. |
|
Defines the columns to accelerate in a table-level rule. Specify all
columns by using |
|
Name of the schema that contains the specified table. |
|
Name of the table that contains the specified column. |
|
The materialization type performed on the specified column in the specified
table. Valid values are |
|
Priority for the warmup rule. To ensure a column is accelerated even if
storage capacity is exceeded, set the |
|
Duration for which the warmup rule remains active. Use |
|
Defaults to all partitions. Use the JSON array syntax |
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)
withREAL
andDOUBLE
data typesin_nan(x)
withREAL
andDOUBLE
data typescast(x as type)
withDOUBLE
cast toREAL
, or any type cast toVARCHAR
cast(x as type)
withDOUBLE
andDECIMAL
data typesday(d)
andday_of_month(d)
withDATE
andTIMESTAMP
data typesday_of_year(d)
anddoy(y)
withDATE
andTIMESTAMP
data typesday_of_week(d)
anddow(d)
withDATE
andTIMESTAMP
data typesyear(d)
withDATE
andTIMESTAMP
data typesyear_of_week(d)
andyow(d)
withDATE
andTIMESTAMP
data typesweek(d)
andweek_of_year(d)
withDATE
andTIMESTAMP
data typesLIKE
andNOT LIKE
withVARCHAR
data typecontains(arr_varchar, value)
with array ofVARCHAR
data typesubstring
andsubstr
withVARCHAR
data typestrpos
withBIGINT
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
.