Treasure Data Time Filtering FAQs

Question 1

What is the difference between relative and absolute time filtering?

Accepted Answer

Relative filtering (td_interval) uses dynamic strings like '-7d' to look back from the current time or a reference point, while absolute filtering (td_time_range) uses fixed start and end timestamps.

Question 2

How do I handle time filtering in scheduled workflows?

Accepted Answer

You should use td_scheduled_time() as a reference point within your time functions to ensure that your relative date ranges are calculated based on when the workflow was supposed to run, rather than the current system time.

Question 3

Does this skill support different timezones?

Accepted Answer

Yes, functions like td_interval, td_time_range, and td_time_string all accept an optional timezone parameter (e.g., 'JST' or 'America/Los_Angeles') to ensure accuracy for regional data processing.

Question 4

Will this skill help reduce my Treasure Data query costs?

Accepted Answer

Yes. By applying correct partition pruning techniques, you limit the amount of data scanned, which directly correlates to lower resource usage and faster query completion times.

Question 5

Why should I use td_interval instead of standard SQL WHERE clauses?

Accepted Answer

Treasure Data's 'time' column is specifically indexed for partition pruning. Using td_interval or td_time_range ensures the query engine only scans relevant data partitions, which is significantly faster and more cost-effective than standard date functions.

Treasure Data Time Filtering

Treasure Data Time Filtering

关于

主要功能

使用场景

关于

主要功能

使用场景