Hive convert string to boolean12/2/2023 In this PySpark article, you have learned how to cast or change one DataFrame column Data Type to another type using withColumn(), selectExpr(), SQL. All the integral numeric types, FLOAT and STRING can be implicitly converted to DOUBLE. This example is also available at GitHub for reference. Hive supports a BOOLEAN type for storing true and false values. Below Spark, snippet changes DataFrame column, age to. withColumn("jobStartDate",col("jobStartDate").cast(DateType())) Change Column Type using withColumn () and cast () To convert the data type of a DataFrame column, Use withColumn () with the original column name as a first argument and for the second argument apply the casting method cast () with DataType on the column. withColumn("isGraduated",col("isGraduated").cast(BooleanType())) \ Spark = ('').getOrCreate()įrom import StringType,BooleanType,DateTypeĭf2 = df.withColumn("age",col("age").cast(StringType())) \ Complete Example of Casting PySpark Columnīelow is complete working example of how to convert the data types of DataFrame column. On SQL just wrap the column with the desired type you want.ĭf3.createOrReplaceTempView("CastExample")ĭf4 = spark.sql("SELECT STRING(age),BOOLEAN(isGraduated),DATE(jobStartDate) from CastExample")ĥ. In order to use on SQL, first, we need to create a table using createOrReplaceTempView(). We can also use PySpark SQL expression to change/cast the spark DataFrame column type. "cast(jobStartDate as string) jobStartDate") "cast(isGraduated as string) isGraduated", SelectExpr() is a function in DataFrame which we can use to convert spark DataFrame column “age” from String to integer, “isGraduated” from boolean to string and “jobStartDate” from date to String.ĭf3 = df2.selectExpr("cast(age as int) age", |- isGraduated: boolean (nullable = true) Use withColumn() to convert the data type of a DataFrame column, This function takes column name you wanted to convert as a first argument and for the second argument apply the casting method cast() with DataType on the column. Hive is designed to enable easy data summarization, ad-hoc querying and analysis of large volumes of data. Hadoop provides massive scale out and fault tolerance capabilities for data storage and processing on commodity hardware. |firstname|age|jobStartDate|isGraduated|gender|salary| Hive is a data warehousing infrastructure based on Apache Hadoop. |- jobStartDate: string (nullable = true) Let’s run with an example, first, create simple DataFrame with different data types. Spark.sql("SELECT INT(age),BOOLEAN(isGraduated),DATE(jobStartDate) from CastExample") From import IntegerType,BooleanType,DateTypeĭf.withColumn("age",df.age.cast(IntegerType()))ĭf.withColumn("age",df.age.cast('integer'))ĭf.select(col("age").cast('int').alias("age"))
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