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Returns a DataFrame containing a new row for each element in the given array or map. Uses the default column name col for elements in the array and key and value for elements in the map unless specified otherwise.
Syntax
spark.tvf.explode(collection)
Parameters
| Parameter | Type | Description |
|---|---|---|
collection |
pyspark.sql.Column |
Target column to work on. |
Returns
pyspark.sql.DataFrame: A DataFrame with a new row for each element.
Examples
Example 1: Exploding an array column
import pyspark.sql.functions as sf
spark.tvf.explode(sf.array(sf.lit(1), sf.lit(2), sf.lit(3))).show()
+---+
|col|
+---+
| 1|
| 2|
| 3|
+---+
Example 2: Exploding a map column
import pyspark.sql.functions as sf
spark.tvf.explode(
sf.create_map(sf.lit("a"), sf.lit("b"), sf.lit("c"), sf.lit("d"))
).show()
+---+-----+
|key|value|
+---+-----+
| a| b|
| c| d|
+---+-----+
Example 3: Exploding an array of struct column
import pyspark.sql.functions as sf
spark.tvf.explode(sf.array(
sf.named_struct(sf.lit("a"), sf.lit(1), sf.lit("b"), sf.lit(2)),
sf.named_struct(sf.lit("a"), sf.lit(3), sf.lit("b"), sf.lit(4))
)).select("col.*").show()
+---+---+
| a| b|
+---+---+
| 1| 2|
| 3| 4|
+---+---+
Example 4: Exploding an empty array column
import pyspark.sql.functions as sf
spark.tvf.explode(sf.array()).show()
+---+
|col|
+---+
+---+
Example 5: Exploding an empty map column
import pyspark.sql.functions as sf
spark.tvf.explode(sf.create_map()).show()
+---+-----+
|key|value|
+---+-----+
+---+-----+