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  1. Mar 27, 2024 · In summary, PySpark SQL function collect_list() and collect_set() aggregates the data into a list and returns an ArrayType. collect_set () de-dupes the data and return unique values whereas collect_list () return the values as is without eliminating the duplicates.

  2. Parameters col Column or str. target column to compute on. Returns Column. list of objects with duplicates. Notes. The function is non-deterministic because the order of collected results depends on the order of the rows which may be non-deterministic after a shuffle.

  3. The collect_list function in PySpark is a powerful tool that allows you to aggregate values from a column into a list. It is particularly useful when you need to group data and preserve the order of elements within each group. With collect_list, you can transform a DataFrame or a Dataset into a new DataFrame where each row represents a group ...

  4. Jul 6, 2024 · To utilize `collect_list` and `collect_set`, you need to import them from the `pyspark.sql.functions` module, as shown below: from pyspark.sql import SparkSession from pyspark.sql.functions import collect_list, collect_set Initializing a SparkSession. The `SparkSession` is the entry point for programming Spark with the Dataset and DataFrame API.

  5. Jun 17, 2024 · The collect_list function in PySpark SQL is an aggregation function that gathers values from a column and converts them into an array. It is particularly useful when you need to reconstruct or aggregate data that has been flattened or transformed using other PySpark SQL functions, such as explode.

  6. Mar 19, 2024 · Both COLLECT_LIST() and COLLECT_SET() are aggregate functions commonly used in PySpark and PySQL to group values from multiple rows into a single list or set, respectively. These functions are ...

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  8. pyspark.sql.functions.collect_list(col: ColumnOrName) → pyspark.sql.column.Column ¶. Aggregate function: returns a list of objects with duplicates. Notes. The function is non-deterministic because the order of collected results depends on the order of the rows which may be non-deterministic after a shuffle. Examples.

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