Need advice about which tool to choose?Ask the StackShare community!
Luigi vs Kissflow: What are the differences?
Luigi: ETL and data flow management library *. It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in; *Kissflow:** Best Workflow Software. It is a workflow tool & business process workflow management software to automate your workflow process.
Luigi and Kissflow belong to "Workflow Manager" category of the tech stack.
Some of the features offered by Luigi are:
- dependency resolution
- workflow management
On the other hand, Kissflow provides the following key features:
- Process Management
- Case Management
- Project Management
Luigi is an open source tool with 12.1K GitHub stars and 1.99K GitHub forks. Here's a link to Luigi's open source repository on GitHub.
I am so confused. I need a tool that will allow me to go to about 10 different URLs to get a list of objects. Those object lists will be hundreds or thousands in length. I then need to get detailed data lists about each object. Those detailed data lists can have hundreds of elements that could be map/reduced somehow. My batch process dies sometimes halfway through which means hours of processing gone, i.e. time wasted. I need something like a directed graph that will keep results of successful data collection and allow me either pragmatically or manually to retry the failed ones some way (0 - forever) times. I want it to then process all the ones that have succeeded or been effectively ignored and load the data store with the aggregation of some couple thousand data-points. I know hitting this many endpoints is not a good practice but I can't put collectors on all the endpoints or anything like that. It is pretty much the only way to get the data.
For a non-streaming approach:
You could consider using more checkpoints throughout your spark jobs. Furthermore, you could consider separating your workload into multiple jobs with an intermittent data store (suggesting cassandra or you may choose based on your choice and availability) to store results , perform aggregations and store results of those.
Spark Job 1 - Fetch Data From 10 URLs and store data and metadata in a data store (cassandra) Spark Job 2..n - Check data store for unprocessed items and continue the aggregation
Alternatively for a streaming approach: Treating your data as stream might be useful also. Spark Streaming allows you to utilize a checkpoint interval - https://spark.apache.org/docs/latest/streaming-programming-guide.html#checkpointing
Pros of Kissflow
Pros of Luigi
- Hadoop Support5
- Open soure1