Running Trino with Alluxio
Trino is an open source distributed SQL query engine for running interactive analytic queries on data at a large scale. This guide describes how to run queries against Trino with Alluxio as a distributed caching layer, for any data storage systems that Alluxio supports (AWS S3, HDFS, Azure Blob Store, NFS, and more). Alluxio allows Trino to access data regardless of the data source and transparently cache frequently accessed data (e.g., tables commonly used) into Alluxio distributed storage. Co-locating Alluxio workers with Trino workers improves data locality and reduces the I/O access latency when other storage systems are remote or the network is slow or congested.
Prerequisites
- Setup Java for Java 11, at least version 11.0.7, 64-bit,as required by Trino
- Setup Python version 2.6.x, 2.7.x, or 3.x, as required by Trino
- Deploy Trino.
This guide is tested with
Trino-352
. - Alluxio has been set up and is running.
- Make sure that the Alluxio client jar is available.
This Alluxio client jar file can be found at
/<PATH_TO_ALLUXIO>/client/alluxio-2.9.0-client.jar
in the tarball downloaded from Alluxio download page. - Make sure that Hive Metastore is running to serve metadata information of Hive tables.
Basic Setup
Configure Trino to connect to Hive Metastore
Trino gets the database and table metadata information (including file system locations) from
the Hive Metastore, via Trino’s Hive connector.
Here is a example Trino configuration file ${Trino_HOME}/etc/catalog/hive.properties
,
for a catalog using the Hive connector, where the metastore is located on localhost
.
connector.name=hive-hadoop2
hive.metastore.uri=thrift://localhost:9083
Distribute the Alluxio client jar to all Trino servers
In order for Trino to be able to communicate with the Alluxio servers, the Alluxio client
jar must be in the classpath of Trino servers.
Put the Alluxio client jar /<PATH_TO_ALLUXIO>/client/alluxio-2.9.0-client.jar
into the directory
${Trino_HOME}/plugin/hive-hadoop2/
(this directory may differ across versions) on all Trino servers. Restart the Trino workers and
coordinator:
$ ${Trino_HOME}/bin/launcher restart
After completing the basic configuration, Trino should be able to access data in Alluxio. To configure more advanced features for Trino (e.g., connect to Alluxio with HA), please follow the instructions at Advanced Setup.
Examples: Use Trino to Query Tables on Alluxio
Create a Hive table on Alluxio
Here is an example to create an internal table in Hive backed by files in Alluxio.
You can download a data file (e.g., ml-100k.zip
) from
http://grouplens.org/datasets/movielens/.
Unzip this file and upload the file u.user
into /ml-100k/
in Alluxio:
$ ./bin/alluxio fs mkdir /ml-100k
$ ./bin/alluxio fs copyFromLocal /path/to/ml-100k/u.user alluxio:///ml-100k
Create an external Hive table pointing to the Alluxio file location.
hive> CREATE TABLE u_user (
userid INT,
age INT,
gender CHAR(1),
occupation STRING,
zipcode STRING)
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '|'
STORED AS TEXTFILE
LOCATION 'alluxio://master_hostname:port/ml-100k';
You can see the directory and files that Hive creates by viewing the Alluxio WebUI at http://master_hostname:19999
Start Hive Metastore
Ensure your Hive Metastore service is running. Hive Metastore listens on port 9083
by
default. If it is not running, execute the following command to start the metastore:
$ ${HIVE_HOME}/bin/hive --service metastore
Start Trino server
Start your Trino server. Trino server runs on port 8080
by default (configurable with
http-server.http.port
in ${Trino_HOME}/etc/config.properties
):
$ ${Trino_HOME}/bin/launcher run
Query tables using Trino
Follow Trino CLI instructions
to download the trino-cli-<Trino_VERSION>-executable.jar
,
rename it to trino
, and make it executable with chmod +x
(sometimes the executable trino
exists in ${trino_HOME}/bin/trino
and you can use it
directly).
Run a single query (replace localhost:8080
with your actual Trino server hostname and port):
$ ./trino --server localhost:8080 --execute "use default; select * from u_user limit 10;" \
--catalog hive --debug
Advanced Setup
Customize Alluxio User Properties
To configure additional Alluxio properties, you can append the conf path (i.e.
${ALLUXIO_HOME}/conf
) containing alluxio-site.properties
to Trino’s JVM config at etc/jvm.config
under Trino folder. The advantage of this approach is to
have all the Alluxio properties set within the same file of alluxio-site.properties
.
...
-Xbootclasspath/a:<path-to-alluxio-conf>
Alternatively, add Alluxio properties to the Hadoop configuration files
(core-site.xml
, hdfs-site.xml
), and use the Trino property hive.config.resources
in the
file ${Trino_HOME}/etc/catalog/hive.properties
to point to the Hadoop resource locations for
every Trino worker.
hive.config.resources=/<PATH_TO_CONF>/core-site.xml,/<PATH_TO_CONF>/hdfs-site.xml
Example: connect to Alluxio with HA
If the Alluxio HA cluster uses internal leader election,
set the Alluxio cluster property appropriately in the
alluxio-site.properties
file which is on the classpath.
alluxio.master.rpc.addresses=master_hostname_1:19998,master_hostname_2:19998,master_hostname_3:19998
Alternatively you can add the property to the Hadoop core-site.xml
configuration
which is contained by hive.config.resources
.
<configuration>
<property>
<name>alluxio.master.rpc.addresses</name>
<value>master_hostname_1:19998,master_hostname_2:19998,master_hostname_3:19998</value>
</property>
</configuration>
For information about how to connect to Alluxio HA cluster using Zookeeper-based leader election, please refer to HA mode client configuration parameters.
Example: change default Alluxio write type
For example, change
alluxio.user.file.writetype.default
from default ASYNC_THROUGH
to CACHE_THROUGH
.
One can specify the property in alluxio-site.properties
and distribute this file to the classpath
of each Trino node:
alluxio.user.file.writetype.default=CACHE_THROUGH
Alternatively, modify conf/hive-site.xml
to include:
<property>
<name>alluxio.user.file.writetype.default</name>
<value>CACHE_THROUGH</value>
</property>
Increase parallelism
Trino’s Hive connector uses the config hive.max-split-size
to control the parallelism of the
query.
For Alluxio 1.6 or earlier, it is recommended to set this size no less than Alluxio’s block
size to avoid the read contention within the same block.
For later Alluxio versions, this is no longer an issue because of Alluxio’s async caching abilities.
Avoid Trino timeouts when reading large files
It is recommended to increase alluxio.user.streaming.data.timeout
to a bigger value (e.g
10min
) to avoid a timeout failure when reading large files from remote workers.