Temp Tables In Redshift

Derik Hammer has some notes on temporary tables in Amazon Redshift:

One difference between regular tables and temporary tables is how they are typically used. Temporary tables are session scoped which means that adding them into a process or report will probably cause them to be created multiple times. Temporary tables might be very similar to regular tables but most regular tables are not re-written into, every time they are queried.

The disk writes involved in populating the temporary table might be more expensive than the reads would be if you were to modify your query to include the logic into one, larger, query. The frequency of the report or process will be a factor into how much of a performance hit you get by using the temporary tables. If you are using temporary tables to make debugging a procedure easier or to enhance readability, make sure you understand the IO cost of performing writes and then reading that data back into a subsequent query.

Read on for more.

Related Posts

Registering SignalR to the Cosmos DB Change Feed

Hasan Savran shows us how we can hook up SignalR to view the Cosmos DB Change Feed: SignalR allows server code to send asynchronous notifications to client-side web applications. By using it, Azure Functions can send real-time messages to your web applications. Prices can get change whenever data changes in database. Notices can be sent […]

Read More

Diagnosing TCP SACKs-Related Slowdown in Databricks

Chris Stevens, et al, walk us through troubleshooting a slowdown after using Linux images which have been patched for the TCP SACKs vulnerabilities: In order to figure out why the straggler task took 15 minutes, we needed to catch it in the act. We reran the benchmark while monitoring the Spark UI, knowing that all […]

Read More

Categories

February 2018
MTWTFSS
« Jan Mar »
 1234
567891011
12131415161718
19202122232425
262728