Adding storage and querying data

In this tutorial, you learn to add a storage that you own and explore how the watsonx.data service interacts with the data you bring in.

Sample Scenario : Your team is working on developing an automated data pipeline that requires querying data from the data bucket that you have. Your manager requests you to retrieve data from the data bucket by using the watsonx.data instance.

For this scenario, you must create the Presto query engine, establish connection with the storage, ingest data to the data bucket and display the result in watsonx.data instance.

Objective

Creating infrastructure within the watsonx.data service.
Establishing connection with the customer data bucket.
Querying from the bucket

Before you begin

This tutorial requires:

Subscription of watsonx.data on cloud.
The configuration details of data bucket that you bring in. This is required for establishing connetion with the watsonx.data.
Provision watsonx.data service instance

Adding the storage that you own and ingesting data

In this section of the tutorial, you learn how to register the storage bucket that you bring and add data to it.

To add a storage bucket that you own, see Adding a storage-catalog pair.
You can use the Create table option from the Data manager page to load local or external sources of data files to create tables. You can also ingest large files by using the CLI. See more Creating an ingestion job by using the configuration file.

Querying data

In this section of the tutorial, you learn how to navigate to the Query workspace, and create SQL queries to query your data from the bucket.

To run SQL query, do the following steps:

From the navigation menu, select SQL. The Query workspace page opens.
Select the Presto (Java) engine from the Engine drop-down.
Select a catalog, for example, default schema, and a table, for example, order_detail, to run the query.
Click the overflow menu and select the required query.
- For a catalog and schema, you can run the Generate Path query.
- For a table, you can run the Generate path, Generate SELECT, Generate ALTER, and Generate DROP query.
- For a column, you can run the Generate path, Generate SELECT, and Generate DROP query.
Consider the following sample query to view the details from the table:

Example:
```
SELECT * FROM "iceberg-beta"."default"."order_detail" LIMIT 10;
```
Click Run on to run the query.
Select the Result set or Details tab to view the results. If required, you can save the query.
Click Saved queries to view the saved queries.
Click Explain to view the logical or distributed plan of execution for a specified SQL query.