09-27-2022 06:58 AM
B1123451020-502,"","{""m"": {""difference"": 60}}","","","",2022-02-12T15:40:00.783Z
B1456741975-266,"","{""m"": {""difference"": 60}}","","","",2022-02-04T17:03:59.566Z
B1789753479-460,"","",",","","",2022-02-18T14:46:57.332Z
B1456741977-123,"","{""m"": {""difference"": 60}}","","","",2022-02-04T17:03:59.566Z
df_inputfile = (spark.read.format("com.databricks.spark.csv")
.option("inferSchema", "true")
.option("header","false")
.option("quotedstring",'\"')
.option("escape",'\"')
.option("multiline","true")
.option("delimiter",",")
.load('<path to csv>'))
print(df_inputfile.count()) # Prints 3
print(df_inputfile.distinct().count()) # Prints 4
I'm trying to read the data above from a CSV file and end up with a wrong count, although the dataframe contains all the expected records. df_inputfile.count() prints 3 although it should have been 4.
It looks like this is happening because of the single comma in the 4th column of the 3rd row. Can someone please explain why?
09-29-2022 11:23 PM
Hi, Could you please check the syntax? '\"' ?
10-04-2022 12:57 AM
Hi Debayan, there's no syntax error in the code snippet. Using .option("escape",'"') makes no difference to the counts. I still get wrong counts.
10-03-2022 12:58 AM
Hi @Tarique Anwer , We haven’t heard from you on the last response from @Debayan Mukherjee and I was checking back to see if his suggestions helped you.
Or else, If you have any solution, please do share that with the community as it can be helpful to others.
Also, Please don't forget to click on the "Select As Best" button whenever the information provided helps resolve your question.
10-04-2022 01:00 AM
Hi @Kaniz Fatma Unfortunately, the suggestion hasn't helped and I've not been able to figure out the reason for the strange results so far.
11-20-2022 07:43 PM
Hi @Tarique Anwer
Hope all is well!
Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help.
We'd love to hear from you.
Thanks!
Join our fast-growing data practitioner and expert community of 80K+ members, ready to discover, help and collaborate together while making meaningful connections.
Click here to register and join today!
Engage in exciting technical discussions, join a group with your peers and meet our Featured Members.