Redshift: Query External Tables Conditionally

by Viktoria Ivanova 46 views

Hey guys! Ever found yourself in a situation where you need to query an external table in Redshift, but you're not sure if the table even exists? It's a common scenario, especially when dealing with dynamic data sources or ETL pipelines. You might want to avoid errors and gracefully handle cases where the table is missing. In this article, we'll dive deep into how to conditionally query external tables in Redshift, ensuring your queries run smoothly and your data pipelines stay robust. We'll explore different approaches, discuss their pros and cons, and provide practical examples you can use in your own projects. So, buckle up and let's get started!

Understanding the Challenge

Before we jump into the solutions, let's clearly define the problem. Imagine you have a Redshift cluster and you're using Spectrum to query data stored in S3. You have a script that runs daily, querying an external table that represents the latest data for the day. However, sometimes the data for a particular day might not be available, and the external table might not exist yet. If you try to query a non-existent table, Redshift will throw an error, and your script will fail.

The challenge is to avoid this error and handle the situation gracefully. You want to check if the external table exists before attempting to query it. If the table exists, you'll proceed with the query. If not, you might want to return a default value, log a message, or take other appropriate actions. The goal is to create a resilient and robust data pipeline that can handle missing tables without crashing.

Here’s the basic idea of what we want to achieve, expressed in SQL-like pseudocode:

SELECT
    CASE
        WHEN (/* Check if table exists */) THEN
            (SELECT COUNT(*) FROM my_external_table)
        ELSE
            0
    END;

The core question is: How do we implement the /* Check if table exists */ part in Redshift? Let's explore different methods to achieve this.

Method 1: Using pg_tables System Catalog

One way to check if a table exists in Redshift is by querying the pg_tables system catalog. This catalog contains information about all the tables in your database, including external tables. You can use it to determine if a table with a specific name exists in a particular schema. This approach is relatively straightforward and leverages Redshift's built-in capabilities. Let’s delve into how it works and see a practical example.

How it Works

The pg_tables system catalog stores metadata about tables, views, and other relational objects in your Redshift database. It includes columns like schemaname, tablename, tableowner, and tabletype. By querying this catalog, you can filter for tables with specific names and schemas. If a row is returned for your table, it means the table exists. If no rows are returned, the table does not exist. This method is efficient because it directly queries Redshift's internal metadata, avoiding the need to access external data sources.

The key columns we'll be using are:

  • schemaname: The name of the schema the table belongs to.
  • tablename: The name of the table.

Practical Example

Here's an example of how you can use pg_tables to check if an external table exists and then conditionally query it:

SELECT
    CASE
        WHEN EXISTS (
            SELECT
                1
            FROM
                pg_tables
            WHERE
                schemaname = 'your_schema'
                AND tablename = 'your_external_table'
        ) THEN (
            SELECT
                COUNT(*)
            FROM
                your_schema.your_external_table
        )
        ELSE 0
    END;

In this example:

  1. We use a CASE statement to conditionally execute different queries.
  2. The WHEN clause uses the EXISTS operator to check if a subquery returns any rows.
  3. The subquery selects from pg_tables, filtering by schemaname and tablename to find the specific external table you're interested in. Replace 'your_schema' and 'your_external_table' with the actual schema and table names.
  4. If the subquery returns a row (i.e., the table exists), the THEN clause executes a SELECT COUNT(*) query against the external table.
  5. If the subquery returns no rows (i.e., the table does not exist), the ELSE clause returns 0.

Pros and Cons

Pros:

  • Simple and straightforward: This method is easy to understand and implement.
  • Efficient: It queries Redshift's internal metadata, which is generally fast.
  • No external dependencies: It doesn't rely on any external tools or services.

Cons:

  • Redshift-specific: This method is specific to Redshift and might not be portable to other database systems.
  • Metadata-dependent: It relies on the accuracy and availability of Redshift's metadata.

Use Cases

This method is ideal for scenarios where you need a quick and easy way to check for the existence of an external table within Redshift. It's particularly useful in ETL pipelines or scheduled queries where you want to handle missing tables gracefully. For instance, if you have a daily job that processes data from an external table, you can use this method to ensure the table exists before attempting to query it.

Method 2: Using TRY Block (Redshift Specific)

Another powerful technique in Redshift for handling errors, including non-existent tables, is the TRY block. This feature allows you to execute a block of code and catch any exceptions that occur, providing a way to gracefully handle errors without crashing your entire query. It's especially useful when dealing with external tables, where the existence of the table might be uncertain. Let's explore how to use TRY blocks to conditionally query external tables.

How it Works

The TRY block in Redshift is similar to try-catch blocks in other programming languages. You enclose the code that might raise an exception within the TRY block. If an exception occurs, Redshift will jump to the CATCH block, where you can handle the error. If no exception occurs, the CATCH block is skipped. This mechanism allows you to gracefully handle errors like querying a non-existent table.

In the context of querying external tables, you can put the SELECT statement inside the TRY block. If the table does not exist, Redshift will raise an exception, and you can catch it in the CATCH block. Inside the CATCH block, you can return a default value or take other appropriate actions.

Practical Example

Here's an example of how to use a TRY block to conditionally query an external table:

CREATE OR REPLACE PROCEDURE check_external_table_exists()
AS $
DECLARE
    table_count INT;
BEGIN
    BEGIN
        SELECT
            COUNT(*)
        INTO
            table_count
        FROM
            your_schema.your_external_table;
    EXCEPTION
        WHEN OTHERS THEN
            table_count := 0;
    END;
    SELECT table_count;
END;
$
LANGUAGE plpgsql;

CALL check_external_table_exists();

In this example:

  1. We create a stored procedure called check_external_table_exists.
  2. Inside the procedure, we declare a variable table_count to store the result.
  3. We use a BEGIN...EXCEPTION...END block, which is the equivalent of a TRY...CATCH block in other languages.
  4. Inside the BEGIN block, we attempt to SELECT COUNT(*) from the external table and store the result in table_count.
  5. If the table does not exist, Redshift will raise an exception, and the control will jump to the EXCEPTION block.
  6. In the EXCEPTION block, we catch any exception (WHEN OTHERS THEN) and set table_count to 0.
  7. Finally, we select the value of table_count, which will be the count from the table if it exists or 0 if it doesn't.
  8. We then call the stored procedure using CALL check_external_table_exists();.

Pros and Cons

Pros:

  • Handles multiple error types: The TRY block can catch any exception, not just the