pyspark.sql.functions.array_max#
- pyspark.sql.functions.array_max(col)[source]#
- Array function: returns the maximum value of the array. - New in version 2.4.0. - Changed in version 3.4.0: Supports Spark Connect. - Parameters
- colColumnor str
- The name of the column or an expression that represents the array. 
 
- col
- Returns
- Column
- A new column that contains the maximum value of each array. 
 
 - Examples - Example 1: Basic usage with integer array - >>> from pyspark.sql import functions as sf >>> df = spark.createDataFrame([([2, 1, 3],), ([None, 10, -1],)], ['data']) >>> df.select(sf.array_max(df.data)).show() +---------------+ |array_max(data)| +---------------+ | 3| | 10| +---------------+ - Example 2: Usage with string array - >>> from pyspark.sql import functions as sf >>> df = spark.createDataFrame([(['apple', 'banana', 'cherry'],)], ['data']) >>> df.select(sf.array_max(df.data)).show() +---------------+ |array_max(data)| +---------------+ | cherry| +---------------+ - Example 3: Usage with mixed type array - >>> from pyspark.sql import functions as sf >>> df = spark.createDataFrame([(['apple', 1, 'cherry'],)], ['data']) >>> df.select(sf.array_max(df.data)).show() +---------------+ |array_max(data)| +---------------+ | cherry| +---------------+ - Example 4: Usage with array of arrays - >>> from pyspark.sql import functions as sf >>> df = spark.createDataFrame([([[2, 1], [3, 4]],)], ['data']) >>> df.select(sf.array_max(df.data)).show() +---------------+ |array_max(data)| +---------------+ | [3, 4]| +---------------+ - Example 5: Usage with empty array - >>> from pyspark.sql import functions as sf >>> from pyspark.sql.types import ArrayType, IntegerType, StructType, StructField >>> schema = StructType([ ... StructField("data", ArrayType(IntegerType()), True) ... ]) >>> df = spark.createDataFrame([([],)], schema=schema) >>> df.select(sf.array_max(df.data)).show() +---------------+ |array_max(data)| +---------------+ | NULL| +---------------+