Hacker News Reader

Comment by rebanevapustus | Hacker News Reader

Big fan of Feldera here.

I would advise everybody to stay clear of anything that isn't Feldera or Materialize. Nobody aside from these guys have a IVM product that is grounded on proper theory.

If you are interested in trying out the theory (DBSP) underneath Feldera, but in Python, then check this out: https://github.com/brurucy/pydbsp

It works with pandas, polars...anything.

View on HN

It's based on Z-Sets - a generalization of relational algebra. Many of the aggregations, projections, filters from SQL are associative and can be implemented in Z-Sets. Z-Sets supports incremental operations (adding one value to a set while computing the 'max' is just the max of the two arguments - rather than requiring recomputing the 'max' over the entire set.

dumb question: how do z-sets or feldera deal with updates to values that were incorporated into the max already?

For example - max over {4, 5} is 5. Now I update the 5 to a 3, so the set becomes {4, 3} with a max of 4. This seems to imply that the z-sets would need to store ALL the values - again, in their internal state.

Also there needs to be some logic somewhere that says that the data structure for updating values in a max aggregation needs to be a heap. Is that all happening somewhere?

Just a guess... wouldl like to hear the answer as well.

they probably have a monotonicity detector somewhere, which can decide whether to keep all the values or discard them. If they keep them, they probably use something like a segment tree to index.

Yes, we do a lot of work with monotonicity detection. It's central to we perform automatic garbage collection based on lateness.

That's right, we perform static dataflow analysis to determine what data can get discarded. GC itself is done lazily as part of LSM tree maintenance. For MAX specifically, we don't have this optimization yet. In the general case, incrementally maintaining the MAX aggregate in the presence of insertions and deletions requires tracking the entire contents of the group, which is what we do. If the collection can be proved to be append-only, then it's sufficient to store only the current max element. This optimization is yet coming to Feldera.

We use monotonicity detection for various things. I believe (can double check) that it's used for max as well. But you're correct that in the general case, max is non-linear, so will need to maintain state.

Update from Leonid on current implementation: each group is ordered by the column on which we compute max, so it's O(1) to pick the last value from the index.

So the writes are O(N) then - to keeps reads at O(1)?

Both reads and writes are O(1) in time complexity. Writes additionally have the log(N) amortized cost of maintaining the LSM tree.

gotcha! thanks for the clarification

> Z-Sets - a generalization of relational algebra

Does this have a paper or some material describing the theory?

This is our paper describing the theory underlying Feldera: https://www.vldb.org/pvldb/vol16/p1601-budiu.pdf

This is pretty neat but I'm wondering how well this implementation obeys dataframe algebra. Ponder goes into detail about how dataframes and relations aren't the same, but your dataframe zset seems to be more or less the exact same thing as the relation zset?

https://youtu.be/7TyIjqvfWto?si=CMFH30DFEWxkltlw&t=1095

It does not. The example I give on the README is only meant to show how easy it is to use it to "streamify" regular relational Dataframe operations.

Reply on news.ycombinator.com