pyspark to split array and get key values

Question

I Have dataframe containing array of key value pairs string, i want to get only keys from the key value Number of key value pairs is dynamic for each row and naming conventions are different.

Sample Input
------+-----+-----+-----+---------------------
|ID    |data| value                          |
+------+-----+-----+--------+-----------------
|e1    |D1  |["K1":"V1","K2":"V2","K3":"V3"] |
|e2    |D2  |["K1":"V1","K3":"V3"]           |
|e3    |D1  |["K1":"V1","K2":"V2"]           |
|e4    |D3  |["K2":"V2","K1":"V1","K3":"V3"] |
+------+-----+-----+--------+-----------------


Expected Result:

------+-----+-----+------
|ID    |data| value     |
+------+-----+-----+----|
|e1    |D1  |[K1|K2|K3] |
|e2    |D2  |[K1|K3]    |
|e3    |D1  |[K1|K2]    |
|e4    |D3  |[K2|K1|K3] |
+------+-----+-----+-----

blackbishop · Accepted Answer · 2020-02-22 15:58:46Z

For Spark 2.4+, use transform function.

For each element of the array, substring the key using substring_index and trim leading and trailing quotes using trim function.

df.show(truncate=False)
#+---+----+------------------------------------+
#|ID |data|value                               |
#+---+----+------------------------------------+
#|e1 |D1  |["K1":"V1", "K2": "V2", "K3": "V3"] |
#|e2 |D2  |["K1": "V1", "K3": "V3"]            |
#|e3 |D1  |["K1": "V1", "K2": "V2"]            |
#|e4 |D3  |["K2": "V2", "K1": "V1", "K3": "V3"]|
#+---+----+------------------------------------+    

new_value = """ transform(value, x -> trim(BOTH '"' FROM substring_index(x, ':', 1))) """
df.withColumn("value", expr(new_value)).show()

#+---+----+------------+
#|ID |data|value       |
#+---+----+------------+
#|e1 |D1  |[K1, K2, K3]|
#|e2 |D2  |[K1, K3]    |
#|e3 |D1  |[K1, K2]    |
#|e4 |D3  |[K2, K1, K3]|
#+---+----+------------+

If you want the result as a string delimited by |, you can use array_join like this:

df.withColumn("value", array_join(expr(new_value), "|")).show()
#+---+----+--------+
#|ID |data|value   |
#+---+----+--------+
#|e1 |D1  |K1|K2|K3|
#|e2 |D2  |K1|K3   |
#|e3 |D1  |K1|K2   |
#|e4 |D3  |K2|K1|K3|
#+---+----+--------+

OO7 · Accepted Answer · 2020-02-25 18:27:24Z

1

You can split the value into array which contains key and value.

df.withColumn("keys", expr('transform(value, keyValue -> trim(split(keyValue, ":")[0]))')).drop("value")

edited Feb 25, 2020 at 18:27

answered Feb 22, 2020 at 18:47

OO7

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1 Comment

OO7 Over a year ago

Right, there is some limitation on arraytype column iterable. So you can change into: df.withColumn("keys", expr('transform(value, keyValue -> trim(split(keyValue, ":")[0]))')).drop("value").

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