How do spark filters work?

How do spark filters work?

In Spark, the Filter function returns a new dataset formed by selecting those elements of the source on which the function returns true. So, it retrieves only the elements that satisfy the given condition.

How do you filter in PySpark DataFrame?


  1. df. filter(condition) : This function returns the new dataframe with the values which satisfies the given condition.
  2. df. column_name. isNotNull() : This function is used to filter the rows that are not NULL/None in the dataframe column.

What is partition pruning spark?

Partition pruning in Spark is a performance optimization that limits the number of files and partitions that Spark reads when querying. After partitioning the data, queries that match certain partition filter criteria improve performance by allowing Spark to only read a subset of the directories and files.

What is push down SQL?

A pushdown is an optimization to improve the performance of a SQL query by moving its processing as close to the data as possible.

What is pushdown computation?

In the theory of computation, a branch of theoretical computer science, a pushdown automaton (PDA) is a type of automaton that employs a stack. A nested stack automaton allows full access, and also allows stacked values to be entire sub-stacks rather than just single finite symbols.

WHAT IS column pruning?

Partition pruning is an essential performance feature for data warehouses. In partition pruning, the optimizer analyzes FROM and WHERE clauses in SQL statements to eliminate unneeded partitions when building the partition access list.

What is Postgres CTE?

In PostgreSQL, the CTE(Common Table Expression) is used as a temporary result set that the user can reference within another SQL statement like SELECT, INSERT, UPDATE or DELETE. CTEs are typically used to simplify complex joins and subqueries in PostgreSQL.

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