Handling corrupted records in spark | PySpark | Databricks
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- เผยแพร่เมื่อ 10 เม.ย. 2023
- In this video I have talked about reading bad records file in spark. I have also talked about the modes present in spark for reading.
Directly connect with me on:- topmate.io/manish_kumar25
Data:-
id,name,age,salary,address,nominee
1,Manish,26,75000,bihar,nominee1
2,Nikita,23,100000,uttarpradesh,nominee2
3,Pritam,22,150000,Bangalore,India,nominee3
4,Prantosh,17,200000,Kolkata,India,nominee4
5,Vikash,31,300000,,nominee5
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your simply super, I am a Azure Solution Architect, but now I would like to start my journey with Data Engineering. I am very lucky that there is such very valuable and appreciable learning opportunity from your channel. Your are really good my dear, explaining concepts in good understandable way with execution. Even I am recommending your videos to my colleagues and friends
Very well explained Sir, Thank you.Keep educating n sharing your knowledge n experience..❤❤❤
very well explained . The way you are first ask the questions and then explain simply. Thank you so much.
I am preparing data engineer interview from your videos 😊
Thank you
You are doing great job
Manish bhai thank you so much for this. Mujhe jo doubts the woh apne aap clear ho rahe, really appreciate this videos bhai.
Hello Manish, I have been following your course from last couple of days and so far I have covered 17 session of Spark Theory and 7 sessions of Spark Practical. Thank You for all your efforts. Before this I have purchased multiple course on python and pyspark but I lost interest in each of the courses as they were monotonous. I'm actively looking for a job change and interviews are on pipeline, and I got the confidence on PySpark after watching your videos. Thank You ❤.
Bahut ache Manish Bhai, I am eagerly waiting for upcoming video ❤
Manish Bhai plz continue the same way now ur following to explain the concept. It will be Crystal clear for every one also helpful to interviews. Over all excellent THX for ur work and efforts in making content.
Best thing about this series is potential interview questions. I can challenge you will not find this none of channels other than this in the entire TH-cam.
Also we can make a separate document consisting of these questions only which will be greatly beneficial during interview preparation.
Glad you enjoy it!
thanks Manish ....very well explained ....This spark series is very top notch
Thanks much Manish for doing this amazing job.
bhaia ye jo approch hai na padhane ka interview questions ke through wo bhot mst hai!🙏
Consistently following your videos, these videos are helping me a ton.
Nice explanation ....All spark session are helpful for me Thanku u manish sir.
Great interview questions ❤
Manish bhai, You are the best teacher.
"khud Jake type Karo Ctrl + Enter marneke liar nahi phada raha huun" Thank you sir !!! ❤
Thank you bro. Big Hug🙂So many things to learn
Thanks Manish please upload upcoming video ASAP
Nice Tutorial!!, I was trying to implement the same but found that "badRecordsPath" option in only a databricks specific feature and I was executing locally in my machine.
Mja aagya bhaiya, thanks
Awesome buai
Manish bad record handling doc share khariya..😊
Thanks Manish! I am studying late night after finishing office. Will make transition to DE soon. Thanks for the video!
same here, cheers to DE .🤞
addicted to this channel
Aap data engineer ke betaj badshah ho ... please ese hi video banate rho
Mujhe bahut Kam chije aati hai bhai. Av to main 1% v jaanta nhi hounga. Bahut kuch hai sikhne and karne ko in DE
Thank you bhai...
you are best
Hi Manish, If we have input csv file and we have not defined any manual schema, then in that case to show corrupted records- do we have to manually define schema for corrupted record column or how to handle that?
12:13 after printing corrupt records... in my case only nomine2,nomine 3 came under the column ..while in videos whole details of id 3 and 4 came. is there any catch here..as i followed same approach
When I tried the same on databricks, I'm getting the other 3 records instead of bad records.
dataset bhi de dijiye Sir sath me so good hands on ho jayega
Hi sir, Your videos are really interesting and the way you are teaching is too easy. One doubt i couldn't find the file link in the description. Could you pls provide the link. May god fulfill all your dreams. Thank you☺
Hi Manish,
When I run only this
df = spark.read.format("csv") \
.option("inferschema", "true") \
.option("header", "true") \
.option("mode", "FAILFAST") \
.load("/FileStore/tables/data.csv")
and then run df.count(), it is showing 5 records in all 3 modes. But when I am running df.show(), it is giving output as per your explanation. What can be the possible reasons for the behavior of the count function?
The count() function in Spark DataFrame counts the number of rows in the DataFrame. It does not specifically check for corrupted or malformed rows when performing the count. In your case, even if there are corrupted rows in the DataFrame, the count() function will still return the total number of rows.
Hello Manish
Hum ab tak flight_csv mein kaam kr rhe the, fir ye smployess_csv kab daalna hai pls guide.
corrupted data and complex data both are same or different in spark?
Manish Ji ...apka concept delivery bahaut acha hai, lekin yad karane ke liye koe document dijiye, kyo ki bar bar video dekhane me time lag raha hai....
Can we do this when reading XML and JSON files
at 12:00 instead of creating whole schema can we create new column using withColumn function? or do we need to create eplicit schema to hangle bad records? could you ans?
Hi Manish, I am getting same records in all three modes. can you please help here
hello sir kya as a freshers bhi this all questions are asked ?
I had a question, let's say if we have a CSV file which has some data in comma lets say address itself has commas so can we pass some text wrap in pyspark? Data can be like "Six Street,Ontario", so how can we pass this because this is not a corrupted record.
bhai....can you please provide the English subtitles too.. just to understand in better way
At 15:32 why only 3 records are shown as the mode is permissive, shouldn't the query fetch all the records ?
Hi manish,
Where we can check employee file
Hi Manish, Nice so;ution
but what if I have 500+ columns in my table, how can I do that then?
Where did we get this CSV file --employee data
where can I get the csv file used
How will spark know that it's bad records. Based on what conditions ,it's deciding it's bad ?
Plz upload your next videos bhaiya 😊
Sure
How to delete created table in SPARK we created?
How to handle corrupted data in parquet file ?
Manish ji, mera ek doubt hai. How corrupt_record column is taking data from the beginning(i.e. ID column)of the row?
column name should be "_corrupt_record"
in permissive mode why it didn't created a new column?
Hi Manish,
I have tried saving the corrupted records to a file, but i am unable to use %fs ls. It shows error - UsageError: Line magic function `%fs` not found. Can you help here?
I converted the text file to CSV, but when printed that same CSV in data bricks a new column i.e. 6th column is generated with null values, so basically I am not getting 3 different table for 3 different modes, what could be possible error ?
most probaly your csv is not created as pe the need check it once while opening csv in notepad it should look like this
id,name,age,salary,address,nominee
1,Manish,26,75000,bihar,nominee1
2,Udit,25,100000,indore,nominee2
3,jiya,15,1500000,lomri , India,nominee2
4,swati,19,200000,kota,nominee4
5,ravi,25,300000,indore ,India,nominee5
6,tanu,25,120000,,nominee6
there should not be any records inside " " and try
Hello Manish Bhai.. CSV file aapne mention nhi kiya description me...please provide krenge kya
Data ko aap copy karke save as csv kar lijiye
there is no csv file in description.
@Manish Kumar, in option are you using columnNameOfCorruptRecord, because otherwise it's not displaying corrupt records.. I don't know how my previous comment got deleted I searched for this option in the internet and it worked for me.
No I didn't use columnNameIfCorruptRecord. I created manual schema and read the schema from there
@@manish_kumar_1 after creating manualSchema, for me it's appearing as extra column and showing records of India for those rows
Same for me
Have you got any solution for this?
why there is 1 job in Permissive mode 3 jobs in DROPMALFORMED and FAILFAST
Where is the spark doccumentation source?
badRecordsPath not getting created in local mode
IllegalArgumentException: If 'badRecordsPath' is specified, 'mode' is not allowed to set. mode: PermissiveMode
This is the error while storing the bad record .
Please advice
Remove the mode from the code
sir i created schema after that in my case it shows in correpted column as nominee why it is shows like this
SAME FOR ME DO YOU GET SOLUTION?
Hi Manish. From where are you learning Scala ?
Scala cookbook
Hi @manish,
After created extra column to store corrupt data, instead of getting whole row i'm getting extra values present in other column like 'nominee3'. while i was watching video i have confusion how whole row of corrupt data stored automatically.
column name should be "_corrupt_record"
@@kavitathorat4451 thanks, got it.
there is other option also i saw where we can load corrupt record in any column we want.
how can we reset our databrick password. i am unable to reset .please suggest
What if we have 100 columns nd we want to print bad records...so in that case it is not possible to create schema manually...any other option to print bad records in that case????
No idea
@shitalkurkure1402 Printing bad records is same as storing it and then view it by converting it to dataframe. Suppose you have 100 columns and it's not possible to create schema manually then store the bad records in required path then view it.
@@soumyaranjanrout2843hey, thank you😊 but for that also we need to write schema manually first.
Sir what happens when our DF is emp_details, in this DF we have total 9 rows, 6 columns, by adding _currpet_Record column in my_schema. How it works/not?, plz xplain.
Id,name,age,sal,add,nomine,
1,raju,17,15000,india,nom1
2,mani,19,21000,usa,nom2
3,Mona,21,31000,usa,nom3
4,rani,32,4100,ind,nom4
5,Mira,25,5000,mum,ind,nom5
6,yoo,21,510,mum,mh,IND,nom6
7,mahi,27,611,hyd,TS,Ind,nom7
8,nani,31,711,hyd,TS,ind,nom1,nom2
9,om,21,911,Pune,mh,ind,nom1,nom2,nom3
i m doing in jupiter noteboo i m i have run the code but data is not getting stored in new column , n=in new column i m only getting null and nomminee 1 and 2 what error or gap can be the reason of this ???
Have you defined your own schema?
@@manish_kumar_1 yes i had
hi manish, facing problem reading the csv file when creating the csv by myself, after running the code, only showing the output, but mode fuction is not working, headers is also not reflecting, probabaly due to incorrect csv file format, can you help me in sharing your csv file so that i can download,that file ,this will help a lot.thanks
Data is already there in description
copy the data and save as from notepad++ to file_name.csv
where is the CSV file ?
how do you trace why a record is corrupt , or capture error while parsing
You will have to check your source that why corrupted data is being pushed
Guys, where can I find the employee file? I have been following the series from first.. not sure where is it. I am not finding data in description.
Check now
@@manish_kumar_1 Thanks!
Bhaiya next video kb ayegi
Day after tomorrow
can you please tell me how to add comments
use # key for single line comment and control+/ for multiple line comments
Not found csv data in description
It's there
Hi where is csv file link ? not able to see in description
Hai to data. Save that as csv file. TH-cam me file daalne ka option nhi hai
Can you release your videos in english ??
I tried but its not shows the seventh column
Send me the complete code
@@manish_kumar_1 done, thank you
where is the Data , csv file
In description
CSV kha hai
Didn't give. I will update it soon
HI @ manish_kumar_1 I tried with the data you provided but I am not able to see the corrupted records based on on different modes and when I created the employee schema and tried to see the corrupted records it is showing all the records under corrupted records.
I am not able to print corrupted records, when I am printing records it forms a new column with nominee value.I am not able to understand what am I doing wrong.
from pyspark.sql.types import StructType,StructField,IntegerType,StringType
emp_schema=StructType([
StructField("id",IntegerType(),True),
StructField("name",StringType(),True),
StructField("age",IntegerType(),True),
StructField("salary",IntegerType(),True),
StructField("address",StringType(),True),
StructField("nominee",StringType(),True),
StructField("corrrecod",StringType(),True)
])
employee_df=spark.read.format("csv")\
.option("header","true")\
.option("inferschema","true")\
.option("mode","PERMISSIVE")\
.schema(emp_schema)\
.load("/FileStore/tables/EmployeeDetails.csv")
employee_df.show(truncate=False)
emp_schema=StructType([
StructField("id",IntegerType(),True),
StructField("name",StringType(),True),
StructField("age",IntegerType(),True),
StructField("salary",IntegerType(),True),
StructField("address",StringType(),True),
StructField("nominee",StringType(),True),
StructField("_corrupt_record",StringType(),True)
])
use this schema. Your schema was not correct.
@@manish_kumar_1 Hi Manish, can you please define the error in his schema, as I was getting the same issue but after copy pasting your schema it worked for me not sure why. Thanks in advance.
@@manish_kumar_1 Got it, we should only use as _corrupt_record as StructField to get the complete record.
@@KotlaMuraliKrishna @dakshitamishra7501 @Mdkaleem__
Manish sir has used column name as _corrupt_record in under StructField .
If you want any other name of column then We have to add the columnNameOfCorruptRecord option as column name which we have given in schema.
Like this:-
emp_schema= StructType(
[
StructField("id",IntegerType(),True),
StructField("name",StringType(),True),
StructField("age",IntegerType(),True),
StructField("salary",IntegerType(),True),
StructField("address",StringType(),True),
StructField("nominee",StringType(),True),
StructField("any_name_of_corrupt_record",StringType(),True)
]
)
employee_df2=spark.read.format("csv")\
.option("header","true")\
.option("inferschema","false")\
.option("mode","PERMISSIVE")\
.schema(emp_schema)\
.option("columnNameOfCorruptRecord", "any_name_of_corrupt_record")\
.load("/FileStore/tables/employee_file.csv")
employee_df2.show()
You can go through this site:-
medium.com/@sasidharan-r/how-to-handle-corrupt-or-bad-record-in-apache-spark-custom-logic-pyspark-aws-430ddec9bb41#:~:text=to%20add%20the-,columnNameOfCorruptRecord,-option%20as%20column
@@KotlaMuraliKrishna did you find any solution for this issue ?
As I'm also getting the same output as yours
why I am getting corrupt record here? Also corrupt record value is only nominee
emp_df = spark.read.format("csv")\
.option("header", "true")\
.option("inferschema","true")\
.schema(emp_schema)\
.option("badRecordsPath","/FileStore/tables/bad_records")\
.load("/FileStore/tables/employee_file.csv")
emp_df.show(truncate = False)
(1) Spark Jobs
emp_df:pyspark.sql.dataframe.DataFrame = [id: integer, name: string ... 5 more fields]
+---+--------+---+------+---------+-------+--------------+
|id |name |age|salary|address |nominee|corrupt_record|
+---+--------+---+------+---------+-------+--------------+
|3 |Pritam |22 |150000|Bangalore|India |nominee3 |
|4 |Prantosh|17 |200000|Kolkata |India |nominee4 |
+---+--------+---+------+---------+-------+--------------+
same doubt i have, even if we add new column extra records value will be placed in that and other have null
there is 2 options
1) keep column name '_corrupt_record'
2) .load("/FileStore/tables/employee_file.csv",ColumnNameOfCorruptRecord='corrupt_record')
Unable to find spark link @manish kumar
Yes I had not given. I will add soon
id,name,age,salary,address,nominee
1,Manish,26,75000,bihar,nominee1
2,Nikita,23,100000,uttarpradesh,nominee2
3,Pritam,22,150000,Bangalore,India,nominee3
4,Prantosh,17,200000,Kolkata,India,nominee4
5,Vikash,31,300000,,nominee5
Employee.csv
Thanks Amlan
@@manish_kumar_1 arre sir Jaan de denge aapke liye...
Instead of bad records it shows me the correct one...
bad_records_df=spark.read.format("json").load("/FileStore/tables/bad_records/20230610T072018/bad_records/")
bad_records_df.show(truncate = False)
|dbfs:/FileStore/tables/employee_df.csv|org.apache.spark.SparkRuntimeException: [MALFORMED_CSV_RECORD] Malformed CSV record: 1,Manish,26,75000,bihar,nominee1 |1,Manish,26,75000,bihar,nominee1 |
|dbfs:/FileStore/tables/employee_df.csv|org.apache.spark.SparkRuntimeException: [MALFORMED_CSV_RECORD] Malformed CSV record: 2,Nikita,23,100000,uttarpradesh,nominee2|2,Nikita,23,100000,uttarpradesh,nominee2|
|dbfs:/FileStore/tables/employee_df.csv|org.apache.spark.SparkRuntimeException: [MALFORMED_CSV_RECORD] Malformed CSV record: 5,Vikash,31,300000,,nominee5 |5,Vikash,31,300000,,nominee5 |
while creating schema, using "_corrupt_record" as the field name.
Sir what happens when our DF is emp_details, in this DF we have total 9 rows, 6 columns, by adding _currpet_Record column in my_schema. How it works/not?, plz xplain.
Id,name,age,sal,add,nomine,
1,raju,17,15000,india,nom1
2,mani,19,21000,usa,nom2
3,Mona,21,31000,usa,nom3
4,rani,32,4100,ind,nom4
5,Mira,25,5000,mum,ind,nom5
6,yoo,21,510,mum,mh,IND,nom6
7,mahi,27,611,hyd,TS,Ind,nom7
8,nani,31,711,hyd,TS,ind,nom1,nom2
9,om,21,911,Pune,mh,ind,nom1,nom2,nom3