11. How to handle corrupt records in pyspark | How to load Bad Data in error file pyspark | #pyspark

how to load only correct records in Apache Spark?
How to handle bad data records in pyspark?
#Databricks #PysparkInterviewQuestions #deltalake
Azure Databricks #spark #pyspark #azuredatabricks #azure
In this video, I discussed many MNC's PySpark scenario based interview questions and answers.

how to handle bad data records in pyspark?
how to load only correct records in pyspark?
columnNameOfCorreptRecord?

10. How to load only correct records in pyspark | How to Handle Bad Data in pyspark #pyspark :

Create dataframe:
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Learn PySpark, an interface for Apache Spark in Python. PySpark is often used for large-scale data processing and machine learning.

Azure data factory tutorial playlist:

ADF interview question & answer:

1. pyspark introduction | pyspark tutorial for beginners | pyspark tutorial for data engineers:

2. what is dataframe in pyspark | dataframe in azure databricks | pyspark tutorial for data engineer:

3. How to read write csv file in PySpark | Databricks Tutorial | pyspark tutorial for data engineer:

4. Different types of write modes in Dataframe using PySpark | pyspark tutorial for data engineers:

5. read data from parquet file in pyspark | write data to parquet file in pyspark:

6. datatypes in PySpark | pyspark data types | pyspark tutorial for beginners:

7. how to define the schema in pyspark | structtype & structfield in pyspark | Pyspark tutorial:

8. how to read CSV file using PySpark | How to read csv file with schema option in pyspark:

9. read json file in pyspark | read nested json file in pyspark | read multiline json file:

10. add, modify, rename and drop columns in dataframe | withcolumn and withcolumnrename in pyspark:

11. filter in pyspark | how to filter dataframe using like operator | like in pyspark:

12. startswith in pyspark | endswith in pyspark | contains in pyspark | pyspark tutorial:

13. isin in pyspark and not isin in pyspark | in and not in in pyspark | pyspark tutorial:

14. select in PySpark | alias in pyspark | azure Databricks #spark #pyspark #azuredatabricks #azure

15. when in pyspark | otherwise in pyspark | alias in pyspark | case statement in pyspark:

16. Null handling in pySpark DataFrame | isNull function in pyspark | isNotNull function in pyspark:

17. fill() & fillna() functions in PySpark | how to replace null values in pyspark | Azure Databrick:

18. GroupBy function in PySpark | agg function in pyspark | aggregate function in pyspark:

19. count function in pyspark | countDistinct function in pyspark | pyspark tutorial for beginners:

20. orderBy in pyspark | sort in pyspark | difference between orderby and sort in pyspark:

21. distinct and dropduplicates in pyspark | how to remove duplicate in pyspark | pyspark tutorial:

[motivational_thoughts]

00:05 Handling corrupt records in PySpark
00:53 Understanding Permissive Mode in PySpark
01:42 Handling corrupt records in PySpark
02:32 Handling corrupt records in PySpark with the 'corrupt record' option.
03:25 Handling corrupt records in PySpark
04:23 Handling corrupt records in PySpark
05:17 Filtering out corrupt records in PySpark
06:12 Separating correct and corrupt records in PySpark

[blessingcrosby-ts]

nice explanation, but can you right code to determine why was the record corrupt