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PQL DELETE()

The Delete() call removes entire records. A row call is used to determine which records will be deleted.

It is potentially a very heavy operation. It iterates over all fields and views in a set of records, removing the records. It also removes all data from fields, existence bits, and key translation for the provided columns for all replicas in the cluster.

Delete() does not support deleting specific fields, only full records based on ROW_CALL. It doesn’t support deletes from Kafka Delete Consumer or two separate clusters.

Note: while you could delete all records in an index using Delete(All()), this is not recommended, as dropping an index would be a much more performant way of deleting all records in an index.

Call Definition 

Delete(ROW_CALL)

Mandatory Arguments

  • ROW_CALL : the row call used to determine which records to delete – i.e. records returned by ROW_CALL will be deleted.

Optional Arguments

Returns

  • boolean
    • true indicates that the columns to delete were found AND deleted.
    • false indicates that the columns to delete were NOT found OR that they WERE found but not deleted.

Examples

Example 1

Delete customers who’s last purchase was before 2021.

Data Pre-Query 

Index: customer (non keyed index)

 _id | age (Int) | has_purchased (Set) | last_purchase (Timestamp)
-----+-----------+---------------------+---------------------------
 0   |    23     | ["brand1","brand2"] | 2021-01-05T08:30:00Z
 1   |    31     | ["brand1","brand3"] | 2020-09-12T12:30:00Z
 2   |    28     | ["brand1","brand3"] | 2021-08-06T16:15:00Z
 3   |    19     | []                  | null
 4   |    25     | ["brand1","brand4"] | 2021-10-01T20:45:00Z
 5   |    40     | ["brand4"]          | 2022-01-13T11:00:00Z

Query 

[customer]Delete(Row(last_purchase < "2021-01-01T00:00:00Z"))

Tabular Response 

 result
--------
 true

Data Post-Query 

 _id | age (Int) | has_purchased (Set) | last_purchase (Timestamp)
-----+-----------+---------------------+---------------------------
 0   |    23     | ["brand1","brand2"] | 2021-01-05T08:30:00Z
 2   |    28     | ["brand1","brand3"] | 2021-08-06T16:15:00Z
 3   |    19     | []                  | null
 4   |    25     | ["brand1","brand4"] | 2021-10-01T20:45:00Z
 5   |    40     | ["brand4"]          | 2022-01-13T11:00:00Z