The data looks like this -
+-----------+-----------+-----------------------------+
| id| point| data|
+-----------------------------------------------------+
| abc| 6|{"key1":"124", "key2": "345"}|
| dfl| 7|{"key1":"777", "key2": "888"}|
| 4bd| 6|{"key1":"111", "key2": "788"}|
I am trying to break it into the following format.
+-----------+-----------+-----------+-----------+
| id| point| key1| key2|
+------------------------------------------------
| abc| 6| 124| 345|
| dfl| 7| 777| 888|
| 4bd| 6| 111| 788|
The explode
function explodes the dataframe into multiple rows. But that is not the desired solution.
Note: This solution does not answers my questions. PySpark "explode" dict in column
As long as you are using Spark version 2.1 or higher, pyspark.sql.functions.from_json
should get you your desired result, but you would need to first define the required schema
from pyspark.sql.functions import from_json, col
from pyspark.sql.types import StructType, StructField, StringType
schema = StructType(
[
StructField('key1', StringType(), True),
StructField('key2', StringType(), True)
]
)
df.withColumn("data", from_json("data", schema))\
.select(col('id'), col('point'), col('data.*'))\
.show()
which should give you
+---+-----+----+----+
| id|point|key1|key2|
+---+-----+----+----+
|abc| 6| 124| 345|
|df1| 7| 777| 888|
|4bd| 6| 111| 788|
+---+-----+----+----+