Project: Alluxio (Runtime / Cloud Native Storage)
File: Trino.md

layout: global title: Running Trino with Alluxio This guide describes how to configure to access Alluxio. 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. Setup Java for Java 11, at least version 11.0.7, 64-bitas required by Trino Setup Python version 2.6.x, 2.7.x, or 3.x, as required by 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 `{{site.ALLUXIOCLIENTJAR_PATH}}` in the tarball downloaded from Alluxio . Make sure that Hive Metastore is running to serve metadata information of Hive tables. 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 `${TRINO_HOME}/etc/catalog/hive.properties`, for a catalog using the Hive connector, where the metastore is located on `localhost`. ```properties connector.name=hive-hadoop2 hive.metastore.uri=thrift://localhost:9083 ``` In order for Trino to be able to communicate with the Alluxio servers, the Alluxio client jar must be in the classpath of Trino servers. Put the Alluxio client jar `{{site.ALLUXIOCLIENTJAR_PATH}}` into the directory `${TRINO_HOME}/plugin/hive-hadoop2/` (this directory may differ across versions) on all Trino servers. Restart the Trino workers and coordinator: ```shell $ ${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 . 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 . Unzip this file and upload the file `u.user` into `/ml-100k/` in Alluxio: ```shell $ ./bin/alluxio fs mkdir /ml-100k $ ./bin/alluxio fs cp file:///path/to/ml-100k/u.user alluxio:///ml-100k ``` Create an external Hive table pointing to the Alluxio file

```sql 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` 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: ```shell $ ${HIVE_HOME}/bin/hive --service metastore ``` Start your Trino server. Trino server runs on port `8080` by default (configurable with `http-server.http.port` in `${TRINO_HOME}/etc/config.properties` ): ```shell $ ${TRINO_HOME}/bin/launcher run ``` Follow to download the `trino-cli-<Trino_VERSION>-executable.jar`, rename it to `trino`, and make it executable with `chmod +x` (sometimes the executable `trino` exists in `${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): ```shell $ ./trino --server localhost:8080 --execute "use default; select * from u_user limit 10;" \ --catalog hive --debug ``` To configure additional Alluxio properties, you can append the conf path (i.e. `${ALLUXIO_HOME}/conf`) containing 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`. ```shell $ -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. ```properties hive.config.resources=/<PATHTOCONF>/core-site.xml,/<PATHTOCONF>/hdfs-site.xml ``` 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. ```properties alluxio.master.rpc.addresses=masterhostname1:19998,masterhostname2:19998,masterhostname3:19998 ``` Alternatively you can add the property to the Hadoop `core-site.xml` configuration which is contained by `hive.config.resources`. ```xml <configuration> <property> <name>alluxio.master.rpc.addresses</name> <value>masterhostname1:19998,masterhostname2:19998,masterhostname3:19998</value> </property> </configuration> ``` For information about how to connect to Alluxio HA cluster using Zookeeper-based leader election, please refer to . For example, change `alluxio.user.file.writetype.default` from default `ASYNCTHROUGH` to `CACHETHROUGH`. One can specify the property in `alluxio-site.properties` and distribute this file to the classpath of each Trino node: ```properties alluxio.user.file.writetype.default=CACHE_THROUGH ``` Alternatively, modify `conf/hive-site.xml` to include: ```xml <property> <name>alluxio.user.file.writetype.default</name> <value>CACHE_THROUGH</value> </property> ``` 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. 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.