Get list of data types from schema in Apache Spark

Question:

I have the following code in Spark-Python to get the list of names from the schema of a DataFrame, which works fine, but how can I get the list of the data types?

columnNames = df.schema.names

For example, something like: 

columnTypes = df.schema.types

Is there any way to get a separate list of the data types contained in a DataFrame schema?

Asked By: User2130

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Source

Answers:

Here’s a suggestion:

df = sqlContext.createDataFrame([('a', 1)])

types = [f.dataType for f in df.schema.fields]

types
> [StringType, LongType]

Reference:

Answered By: Daniel de Paula

Since the question title is not python-specific, I’ll add scala version here:

val types = df.schema.fields.map(f => f.dataType)

It will result in an array of org.apache.spark.sql.types.DataType.

Answered By: Viacheslav Shalamov

Use schema.dtypes

scala> val df = Seq(("ABC",10,20.4)).toDF("a","b","c")
df: org.apache.spark.sql.DataFrame = [a: string, b: int ... 1 more field]

scala>

scala> df.printSchema
root
 |-- a: string (nullable = true)
 |-- b: integer (nullable = false)
 |-- c: double (nullable = false)

scala> df.dtypes
res2: Array[(String, String)] = Array((a,StringType), (b,IntegerType), (c,DoubleType))

scala> df.dtypes.map(_._2).toSet
res3: scala.collection.immutable.Set[String] = Set(StringType, IntegerType, DoubleType)

scala>
Answered By: stack0114106