Configuring Trino on Amazon EMR
Configuring connectors for Trino
Connecting to Amazon Glue as your Hive metastore
It's important and useful to understand that you can configure Amazon Glue Data Catalog as your Hive metastore when running queries with Trino. For additional information, including steps to set up a cluster with a Hive metastore, see Using the Amazon Glue Data Catalog as the metastore for Hive.
For information on integrating EMR on EKS with Amazon Glue, see the following best practices,
EMR Containers integration with Amazon Glue
Connecting to Iceberg tables when using Trino with Amazon EMR
Iceberg is an open table format for analytic tables. It was created for engines like Spark and Trino to query big data from the same tables, using SQL queries. It includes features like isolating data reads and writes, so a reader can avoid querying data that's partially updated, for instance. It also supports state features, like snapshots. It provides an abstraction layer through the use of metadata and manifest files. These describe table schema and make it easy to query data without having to know a lot of details about how it's formatted or organized. When you're connected you can both read data from the tables update data, or write new data to the underlying files.
There's a workshop available that shows you how to configure Iceberg tables with Amazon EMR and Amazon Glue. For more information, see
Analytics Workshop - Set Up and Use Apache Iceberg Tables on Your Data Lake
Connecting with Clients
You can connect with Trino using an available JDBC driver. For more information, see JDBC driver
Monitoring
You can monitor Amazon EMR clusters through the Amazon Web Services Management Console. For more information, see View and monitor an Amazon EMR cluster as it performs work. Amazon EMR also sends its monitoring metrics to Amazon CloudWatch. For more information about monitoring an Amazon EMR cluster, see Amazon CloudWatch events and metrics from Amazon EMR.