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from pyspark.sql.types import * | |
from pyspark.sql.functions import * | |
#Flatten array of structs and structs | |
def flatten(df): | |
# compute Complex Fields (Lists and Structs) in Schema | |
complex_fields = dict([(field.name, field.dataType) | |
for field in df.schema.fields | |
if type(field.dataType) == ArrayType or type(field.dataType) == StructType]) | |
while len(complex_fields)!=0: | |
col_name=list(complex_fields.keys())[0] | |
print ("Processing :"+col_name+" Type : "+str(type(complex_fields[col_name]))) | |
# if StructType then convert all sub element to columns. | |
# i.e. flatten structs | |
if (type(complex_fields[col_name]) == StructType): | |
expanded = [col(col_name+'.'+k).alias(col_name+'_'+k) for k in [ n.name for n in complex_fields[col_name]]] | |
df=df.select("*", *expanded).drop(col_name) | |
# if ArrayType then add the Array Elements as Rows using the explode function | |
# i.e. explode Arrays | |
elif (type(complex_fields[col_name]) == ArrayType): | |
df=df.withColumn(col_name,explode_outer(col_name)) | |
# recompute remaining Complex Fields in Schema | |
complex_fields = dict([(field.name, field.dataType) | |
for field in df.schema.fields | |
if type(field.dataType) == ArrayType or type(field.dataType) == StructType]) | |
return df | |
df=flatten(df) | |
df.printSchema() |
Hello, I tried to use mapType in Spark Streaming but it's not working due to an issue in the code.
Below is the one giving issue while doing in Spark Streaming :
keys = list(map(lambda row: row[0], keys_df.collect()))
Please let me know the best option to resolve it in Spark Structure Steaming.
This function flatten(), fails when there is nested array inside array, It failed to flatten these, "user_mentions": [
{
"screen_name": "AshJone15461246",
"name": "Ash Jones",
"id": 1589564629369462800,
"id_str": "1589564629369462784",
"indices": [
0,
16
]
},
{
"screen_name": "BariAWilliams",
"name": "Bärí A. Williams, Esq.",
"id": 4639656854,
"id_str": "4639656854",
"indices": [
17,
31
]
},
{
"screen_name": "bjorn_hefnoll",
"name": "Björn",
"id": 1374096417954881500,
"id_str": "1374096417954881548",
"indices": [
32,
46
]
},
{
"screen_name": "SpencerAlthouse",
"name": "Spencer Althouse",
"id": 38307346,
"id_str": "38307346",
"indices": [
47,
63
]
}
].
Thanks a lot for your work, it works great.