30. arrayType, array_contains() in pyspark | array in pyspark | Azure Databricks Tutorial | PySpark

Azure Databricks #spark #pyspark #azuredatabricks #azure
In this video, I discussed how to use arrayType, array(), array_contains() functions in pyspark.

1. arrayType datatype in pyspark
2. array function in pyspark
3. array_contains function in pyspark

Create dataframe:
======================================================
from pyspark.sql.types import StringType, ArrayType,StructType,StructField
data = [
("James,,Smith",["ADF","Scala","Pyspark"],["Pyspark","ADF"],"OH","CA"),
("Michael,Rose,",["ADF","SQL","Pyspark"],["ADF","SQL"],"NY","NJ"),
("Robert,,Williams",["SQL","SSIS"],["SQL","SSIS"],"UT","NV")
]
schema = StructType([
StructField("name",StringType(),True),
StructField("skills",ArrayType(StringType()),True),
StructField("workprofile",ArrayType(StringType()),True),
StructField("currentState", StringType(), True),
StructField("previousState", StringType(), True)
])
df = spark.createDataFrame(data=data,schema=schema)
display(df)
-----------------------------------------------------------------------------------------------------------------------
from pyspark.sql.functions import *
df1=df.withColumn('States',array(df.currentState,df.previousState))
display(df1)
---------------------------------------------------------------------------------------------------------------------
df2=df.withColumn('array_contains',array_contains(df.skills,'ADF'))
display(df2)
============================================================

Learn PySpark, an interface for Apache Spark in Python. PySpark is often used for large-scale data processing and machine learning.

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