Any good alternatives for Sqoop? I feel that an ETL tool just for HDFS is too limiting and leads to further fragmentation on the data pipeline.
Using Sqoop from something like Luigi as the ETL manager is a pretty great workflow - https://github.com/spotify/luigi You can define dependencies between jobs based on output file which allows you to re-run only part of your pipeline
How we run Spark and Sqoop in production
11–19 of 19 posts
Re: How we run Spark and Sqoop in production
#12Any good alternatives for Sqoop? I feel that an ETL tool just for HDFS is too limiting and leads to further fragmentation on the data pipeline.
Re: How we run Spark and Sqoop in production
#13Earlier quoted context omitted.
Using Sqoop from something like Luigi as the ETL manager is a pretty great workflow - https://github.com/spotify/luigi You can define dependencies between jobs based on output file which allows you to re-run only part of your pipeline
Thats a great idea - but could you elaborate on the scheduling of jobs on Luigi - it does not have a scheduler like AirFlow - how do you schedule Luigi tasks ?
Re: How we run Spark and Sqoop in production
#14hey all, feel free to reach out to me either on this thread, or directly at nate[at]thumbtack.com if I can answer any questions!
Re: How we run Spark and Sqoop in production
#15Re: How we run Spark and Sqoop in production
#16Earlier quoted context omitted.
Using Sqoop from something like Luigi as the ETL manager is a pretty great workflow - https://github.com/spotify/luigi You can define dependencies between jobs based on output file which allows you to re-run only part of your pipeline
Thats a great idea - but could you elaborate on the scheduling of jobs on Luigi - it does not have a scheduler like AirFlow - how do you schedule Luigi tasks ?