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Temporal filters

Temporal filters allow you to filter data based on time intervals, which are used to retrieve data within a specific time range. Temporal filters will enable you to filter data based on a particular time, such as the current time, a specific date, or a range of dates. By using temporal filters, you can ensure that your queries only return data relevant to the period you are interested in, making your data analysis more accurate and efficient.

Syntax

The temporal filter is an expression using NOW(). It can only be used in the WHERE and HAVING clauses in the query.

An valid temporal filter comprises the following components:

  • A comparison operator, including <, >, <=, >=, = and BETWEEN
  • A time expression of the columns in the base relation as the left side
  • A time expression with NOW() +/- interval as the right side

There could be multiple temporal filters and other expressions in the WHERE clause connected with the AND operator.

-- Allowed
t > NOW() - INTERVAL '1 hour' AND t < NOW() + INTERVAL '1 hour' AND a < 1

A temporal filter condition cannot be connected with another temporal filter using the OR operator, but connecting it with a normal expression is allowed. See the examples below:

-- Allowed
t > NOW() - INTERVAL '1 hour' OR t IS NULL OR a < 1

-- Invalid
t > NOW() - INTERVAL '1 hour' OR t < NOW() - INTERVAL '1 hour'

-- Invalid
(a < 1) OR (t > NOW() - INTERVAL '1 hour' AND t < NOW() - INTERVAL '1')

Also, in the WHERE clause, each expression connected by the AND operator should have only one temporal filter connected with OR expression.

-- Invalid
(t < NOW() - INTERVAL '1 hour' OR t > NOW() OR a < 1)
AND (t < NOW() - INTERVAL '1 hour' OR a < 1)

Usage 1: Delete and clean expired data

When the time expression with NOW() is the lower bound condition of the base relation, such as t > NOW() - INTERVAL '1 hour', it can filter records with event times that are too old.

The following query returns all rows from the sales table where the sale_date column plus one week is greater than the current date and time. In other words, it will return all sales records within the past week.

SELECT * 
FROM sales
WHERE sale_date > NOW() - INTERVAL '1 week';

The temporal filter in this query is sale_date > NOW() - INTERVAL '1 week'. It filters the rows based on the sale_date column and checks if it is within one week of the current time or NOW().

The following query returns all rows from the user_sessions table where the sum of the last_active timestamp and double the session_timeout duration is greater than the current timestamp, indicating active user sessions. This query could be used to clean up old user sessions from the database by deleting any rows that no longer satisfy the condition.

SELECT * 
FROM user_sessions
WHERE last_active + session_timeout * 2 > NOW();

The temporal filter in this query is in the WHERE clause. It checks whether the timestamp of the last activity plus twice the session timeout is greater than the current time or NOW(). This indicates that the session is still active.

Usage 2: Delay table changes

When the time expression with NOW() is the upper bound condition of the base relation such as ts + interval '1 hour' < now(), it can "delay" the table's changes of the input relation. It could be useful when used with the Temporal Join.

Here is a typical example of the temporal join used to widen a fact table.

  CREATE SOURCE fact(id1 INT, a1 INT, p_time TIMESTAMPTZ AS proctime()) WITH (connector = 'kafka', ...);
CREATE TABLE dimension(id2 INT, a2 INT, PRIMARY KEY (id2)) WITH (connector = 'jdbc', ...);
CREATE MATERIALIZED VIEW mv AS SELECT id1, a1, a2 FROM fact LEFT JOIN dimension FOR SYSTEM_TIME AS OF PROCTIME() ON id1 = id2;

However, due to delays caused by the network or other phases, it is not guaranteed that when the record of the fact arrives, the corresponding record in the dimension table has arrived. Therefore, a temporal filter can be set on the fact source to introduce a delay and wait for the dimension table's changes.

  CREATE MATERIALIZED VIEW mv AS 
SELECT
id1, a1, a2
FROM (
-- Delay the source for 5 seconds
SELECT * FROM fact WHERE fact.p_time + INTERVAL '5' SECOND < NOW()
) fact
LEFT JOIN dimension FOR SYSTEM_TIME AS OF PROCTIME() ON id1 = id2;
note

Currently, RisingWave's optimizer cannot ensure the temporal filter's predicate pushdown. Please add the temporal filter in the FROM clause as a sub-query, like the SQL example, instead of writing the temporal filter in the query's top WHERE clause.

info

The PROCTIME in the example can be replaced with the event time in the records.

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