Apache Spark AWS S3 track status of processed files
I need to do the periodical batches ETL jobs over the files stored on AWS S3.
In order to not process the same files twice, I need to keep file status somewhere, for example in some RDBMS.. let's say AWS RDS for PostgreSQL.
For example, I'll create the following table:
|file_name | status |
|-----------------------|
|file1.csv | pending |
|file2.json| pending |
At the very beginning of Apache Spark on AWS EMR application, I'll read all files in pending state from the mentioned table and ETL them. When for example, the ETL for file1.csv will be completed I need to mark it as completed in PostgreSQL table. Something like this:
|file_name | status |
|-----------------------|
|file1.csv | completed |
|file2.json| pending |
AFAIK, Spark doesn't support UPDATE operation for JDBC so I think something is probably wrong with my system design. If so, could you please suggest how to correctly track the processed files on S3 in order to not process them again on new ETL batch run?
apache-spark amazon-s3 amazon-emr
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
add a comment |
I need to do the periodical batches ETL jobs over the files stored on AWS S3.
In order to not process the same files twice, I need to keep file status somewhere, for example in some RDBMS.. let's say AWS RDS for PostgreSQL.
For example, I'll create the following table:
|file_name | status |
|-----------------------|
|file1.csv | pending |
|file2.json| pending |
At the very beginning of Apache Spark on AWS EMR application, I'll read all files in pending state from the mentioned table and ETL them. When for example, the ETL for file1.csv will be completed I need to mark it as completed in PostgreSQL table. Something like this:
|file_name | status |
|-----------------------|
|file1.csv | completed |
|file2.json| pending |
AFAIK, Spark doesn't support UPDATE operation for JDBC so I think something is probably wrong with my system design. If so, could you please suggest how to correctly track the processed files on S3 in order to not process them again on new ETL batch run?
apache-spark amazon-s3 amazon-emr
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
add a comment |
I need to do the periodical batches ETL jobs over the files stored on AWS S3.
In order to not process the same files twice, I need to keep file status somewhere, for example in some RDBMS.. let's say AWS RDS for PostgreSQL.
For example, I'll create the following table:
|file_name | status |
|-----------------------|
|file1.csv | pending |
|file2.json| pending |
At the very beginning of Apache Spark on AWS EMR application, I'll read all files in pending state from the mentioned table and ETL them. When for example, the ETL for file1.csv will be completed I need to mark it as completed in PostgreSQL table. Something like this:
|file_name | status |
|-----------------------|
|file1.csv | completed |
|file2.json| pending |
AFAIK, Spark doesn't support UPDATE operation for JDBC so I think something is probably wrong with my system design. If so, could you please suggest how to correctly track the processed files on S3 in order to not process them again on new ETL batch run?
apache-spark amazon-s3 amazon-emr
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
I need to do the periodical batches ETL jobs over the files stored on AWS S3.
In order to not process the same files twice, I need to keep file status somewhere, for example in some RDBMS.. let's say AWS RDS for PostgreSQL.
For example, I'll create the following table:
|file_name | status |
|-----------------------|
|file1.csv | pending |
|file2.json| pending |
At the very beginning of Apache Spark on AWS EMR application, I'll read all files in pending state from the mentioned table and ETL them. When for example, the ETL for file1.csv will be completed I need to mark it as completed in PostgreSQL table. Something like this:
|file_name | status |
|-----------------------|
|file1.csv | completed |
|file2.json| pending |
AFAIK, Spark doesn't support UPDATE operation for JDBC so I think something is probably wrong with my system design. If so, could you please suggest how to correctly track the processed files on S3 in order to not process them again on new ETL batch run?
apache-spark amazon-s3 amazon-emr
apache-spark amazon-s3 amazon-emr
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
asked Nov 15 '18 at 18:43
alexanoidalexanoid
7,6621388194
7,6621388194
add a comment |
add a comment |
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