How is time series data stored and queried in Cassandra?

9 months ago

Olivia Parker

2 minutes

In Cassandra, time series data can be stored using columns with timestamps. A common approach is to use timestamps as part of the row key, and then store the time series data in column families. CQL (Cassandra Query Language) can be used to query this time series data.

Here is an example of a table structure used to store time series data.

CREATE TABLE time_series_data (
    sensor_id UUID,
    timestamp TIMESTAMP,
    value DOUBLE,
    PRIMARY KEY (sensor_id, timestamp)
);

In this example, the table time_series_data consists of columns sensor_id, timestamp, and value. The sensor_id is used as the partition key, while the timestamp is used as the sorting key. This ensures that the data is partitioned by sensor_id and sorted by timestamp.

To query time series data, you can use CQL statements similar to the following:

SELECT * FROM time_series_data
WHERE sensor_id = ? AND timestamp >= ? AND timestamp <= ?;

This will return time series data for a specific sensor_id within the given start and end timestamps.

Another method for querying time series data is to use Cassandra’s aggregation feature. For example, you can calculate the average value of a specific sensor_id using the following CQL statement:

SELECT AVG(value) FROM time_series_data
WHERE sensor_id = ? AND timestamp >= ? AND timestamp <= ?;

This will return the average of the value column for the specified sensor_id within the given time range.

In general, storing and querying time series data in Cassandra involves selecting the right table structure (using timestamps as part of columns), using the correct query statements to retrieve data, and using aggregation functions as needed to calculate summary information.