pyspark.sql.DataFrame.explain

DataFrame.explain(extended: Union[bool, str, None] = None, mode: Optional[str] = None) → None[source]

Prints the (logical and physical) plans to the console for debugging purposes.

New in version 1.3.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters
extendedbool, optional

default False. If False, prints only the physical plan. When this is a string without specifying the mode, it works as the mode is specified.

modestr, optional

specifies the expected output format of plans.

  • simple: Print only a physical plan.

  • extended: Print both logical and physical plans.

  • codegen: Print a physical plan and generated codes if they are available.

  • cost: Print a logical plan and statistics if they are available.

  • formatted: Split explain output into two sections: a physical plan outline and node details.

Changed in version 3.0.0: Added optional argument mode to specify the expected output format of plans.

Examples

>>> df = spark.createDataFrame(
...     [(14, "Tom"), (23, "Alice"), (16, "Bob")], ["age", "name"])

Print out the physical plan only (default).

>>> df.explain()  
== Physical Plan ==
*(1) Scan ExistingRDD[age...,name...]

Print out all of the parsed, analyzed, optimized and physical plans.

>>> df.explain(True)
== Parsed Logical Plan ==
...
== Analyzed Logical Plan ==
...
== Optimized Logical Plan ==
...
== Physical Plan ==
...

Print out the plans with two sections: a physical plan outline and node details

>>> df.explain(mode="formatted")  
== Physical Plan ==
* Scan ExistingRDD (...)
(1) Scan ExistingRDD [codegen id : ...]
Output [2]: [age..., name...]
...

Print a logical plan and statistics if they are available.

>>> df.explain("cost")
== Optimized Logical Plan ==
...Statistics...
...
pyspark.sql.DataFrame.exceptAll pyspark.sql.DataFrame.fillna