- When to use partitions
- Considerations for partitioning and query performance
- Defining partition keys
- Dropping partitions
Partitions are smaller physical parts of large fact and dimension tables. Partitions provide the first layer of sorting when you ingest data. Data is sorted in storage by partition first, and then pruned and sorted by the primary index definition next. When new data is ingested into a table, Firebolt saves rows automatically in the appropriate partition.
Partitions are particularly useful to simplify table maintenance by allowing you to drop partitions and delete rows in bulk. For example, consider a transaction table with an average of approximately 150,000 transactions a day, which you partition by month. At the end of each month, you can run ALTER TABLE…DROP PARTITION to delete the last month’s data, and then INSERT to update the fact table with the most recent month’s data.
Dropping a partition deletes all the records stored in the partition.
Although some applications may see a performance boost from partitions, Firebolt does not rely on partitioning for performance. Firebolt’s indexing features are enough for many applications.
We recommend that you benchmark your application with and without partitions.
We recommend that you consider partitioning only for tables greater than 100 million rows.
Too many small partitions to read increases I/O and decreases performance. In addition, skewed (asymmetrically distributed) partitions can lead to poor performance. Choose columns for partition keys that create large partitions of relatively equal size.
You define partitions using the PARTITION BY clause in a
CREATE TABLE statement.
Rows with the same value in the column key and whose function expression resolves to the same value are included in the partition.
Partition key arguments must not evaluate to
NULL and can be any of the following.
- Column names, as shown below.
PARTITION BY date_column;
PARTITION BY product_type;
- The result of an EXTRACT function applied to a column of any of the date and time data types, as shown below.
PARTITION BY EXTRACT(MONTH FROM date_column);
- A composite key, with a mix of columns and
EXTRACTfunctions, as shown below.
PARTITION BY EXTRACT(MONTH FROM date_column), product_type;
Floating point data type columns are not supported as partition keys.
Use the ALTER TABLE…DROP PARTITION statement to delete a partition and the data stored in that partition.
When you drop a partition created with a composite partition key, you must specify the full partition key. Dropping based on a subset of a composite key is not supported. See the example Partition and drop by composite key below.
ALTER TABLE <table_name> DROP PARTITION 12,34;
Dropping a partition deletes the partition and the data stored in that partition.
- Partition and drop by date
- Partition and drop by date extraction
- Partition and drop by integer
- Partition and drop by composite key
The examples in this section are based on the following common
CREATE TABLE example. Each example is based on the addition of the
PARTITION BY statement shown.
CREATE FACT TABLE fct_tbl_transactions ( transaction_id BIGINT, transaction_date DATE, store_id INT, product_id INT, units_sold INT ) PRIMARY INDEX store_id, product_id <examples of PARTITION BY clauses below>
The example below creates a partition for each group of records with the same date value in
PARTITION BY transaction_date
The example below drops the partition for records with the date
2020-01-01. The date is provided as a string literal and must be cast to the
DATE data type in the command. The command uses the :: operator for CAST.
ALTER TABLE fct_tbl_transactions DROP PARTITION '2020-01-01'::DATE;
The example below uses
EXTRACT to create a partition for each group of records with the same year value in
PARTITION BY EXTRACT(YEAR FROM transaction_date), EXTRACT(MONTH FROM transaction_date);
The example below drops the partition for records where
3, which corresponds to the month of March. The month is specified as an integer in the command.
ALTER TABLE fct_tbl_transactions DROP PARTITION 2022,04;
The example below creates a partition for each group of records with the same value for
PARTITION BY product_id
The example below drops the partition where
ALTER TABLE fct_tbl_transactions DROP PARTITION 8188;
The example below creates a partition for each group of records where
store_id is the same value and
transaction_date is the same year.
PARTITION BY store_id,EXTRACT(YEAR FROM transaction_date);
The example below drops the partition where
ALTER TABLE transactions DROP PARTITION 982,2020;