RisingWave is a distributed SQL database for stream processing written in Rust. As a developer of RisingWave, I’m always excited (and also a little bit overwhelmed) about its progress every day.

So why not share the excitement with more people (and also help myself to get a better understanding)? That’s why I decided to write this blog post about what’s happening in the project. Hope you will enjoy it!

This blog series is my personal comments about (part of) the development of RisingWave.

Please take it as an unofficial and no-promise supplement.

Most exciting things 🤩

Huge reduce of CI time

As my last post mentioned, last week I found some stupidly effective ways to optimize Rust compile time. I managed to reduce the CI time from main 40min/PR 25min30s to main 28min/PR 16-19min, and it looks good this week!

It’s quite a DX improvement. I’m very happy and would like to quote matklad’s blog again:

Compilation time is a multiplier for basically everything. Whether you want to ship more features, to make code faster, to adapt to a change of requirements, or to attract new contributors, build time is a factor in that.

It also is a non-linear factor. Just waiting for the compiler is the smaller problem. The big one is losing the state of the flow or (worse) mental context switch to do something else while the code is compiling. One minute of work for the compiler wastes more than one minute of work for the human.

Let’s take some time to prevent “broken windows”. The effort would pay off!

DDL UX improvements

DDL can take very long time if there are already a lot of existing data to consume. Previously you can only sit there and wait. But now, you can:

dev=> select * from rw_catalog.rw_ddl_progress;
  ddl_id |         ddl_statement         | progress
    1026 | CREATE INDEX idx ON sbtest1(c) | 69.02%
(1 row)

Most intersting things 😄

OpenDAL into RisingWave!

OpenDAL is a unified data access layer which aims to help access data freely, painlessly, and efficiently.

Previously, RisingWave only supports s3 as a storage backend (and also support other s3-compatible storage). Recently we are trying to add more storage backends.

Last week, we used OpenDAL to add support for using HDFS as a storage backend. This week, we tried more things:

  • Tried using google cloud storage in RisingWave (by wcy-fdu #7920). In our initial benchmark, it seems OpenDAL can be faster than s3-compatible protocol!
  • Changed the implementation for oss from s3-compatible mode to OpenDAL (by wcy-fdu #7969). S3-compatible mode for oss doesn’t support delete_objects, and also suffers from some unstable issues.

It seems that OpenDAL is quite promising!

Rusty stuff 🦀️

We ❤️ Rust! This section is about some general Rust related issues.


Compared with or , The or_else methods on Option and Result can help to avoid expensive computation in the None or Err case. (i.e., lazy evaluation!) And the clippy::or_fun_call lint is for detecting that. It used to be warn by default, but unfortunately it seems to have a high false positive rate, and is now allow by default.

But we met a case where it’s very wanted. In a function, we used ok_or::<RwError> 9 times, so 9 RwError is created regardless of whether it’s needed. But constructing RwError is very expensive because it captures the backtrace…

What’s worse, on M1 Mac, capturing backtrace is VERY SLOW (~300ms #6131) and can even cause SEGFAULT (#6205)! 😇 It’s not completely resolved yet. We mitigated it by reducing unncessary backtrace capturing, but it’s still a problem.

So for this issue, of course we should use ok_or_else instead (by xxchan #7945).

zip_eq & ExactSizeIterator

zip_eq is a safer version of zip which checks if the two iterators have the same length. However, it’s notoriously slow (see #6856 by wangrunji0408 for a benchmark), because in the naive implementation, every item in the iterator is checked.

There’s a ExactSizeIterator trait and naturally it can have an optimized implementation. Such speciallized implementation does not exist because Rust doesn’t support specialization yet. (See tracking issue for specialization (RFC 1210))

So last week I added two new separated traits to replace zip_eq : (code here)

  • zip_eq_debug: uses zip_eq when debug_assertions is enabled, otherwise use zip. It’s a good trade-off between safety and performance, and can be a drop-in replacement for zip_eq.
  • zip_eq_fast: speciallized implementation for ExactSizeIterator. (Actually zip_eq_debug can be good enough, but I still added this after playing with specialization for a while. Just for fun…!😄)

This week, ExactSizeIterator are implemented for more our iterator implementations, so we can use zip_eq_fast more often… (by BugenZhao #7939)

Other notable things

System Parameters

Recently we are doing a large refactoring for system parameters in order to achive consistency and mutability for the cluster configurations (Tracking Issue #7381). This is a serious issue as RisingWave grows mature.

This week, the meta part for ALTER SYTEM is implemented by Gun9niR #7954.


Since RisingWave is PostgreSQL compatible, I had thought that supporting other database tools would be easy. But it turns out to be very hard 😭. The largest obstacles is that database tools ususally rely heavily on the system tables in pg_catalog to get the metadata of the database so that they can provide a better UX. But there are so many features in the system tables!

We have been constantly making efforts to support more and more system tables in order to integrate RisingWave into other tools. This week, we:

  • Added pg_catalog.pg_conversion by yezizp2012 #7964. This is for DBeaver support.
  • Found it’s not possible to add typarray column in pg_catalog.pg_type #7555, which affects sqlalchemy support. But sqlalchemy-risingwave can be used as a substitute for the PG native plugin.

EXPLAIN format

EXPLAIN format is another thing I had thought would be easy. Although current situation is not so bad, it’s still far from perfect.

This week, we tried to use a “global expression id” to make the plan more readable, but it still has some problems:

By the way, here’s another intersting stuff: rewrite the EXPLAIN implementation using the (modified) Wadler-style algebraic pretty printer! See the RFC by ice1000

Query optimizer

Although OLAP batch queries are not the main focus of RisingWave, we still want to make it better. This week, we have these optimizer improvements to make batch queries faster:

We are also trying to add constant relation in streaming (#7854). As a first step, we are doing “plan-level constant folding”, e.g., merge Union with Values inputs into Values by jon-chuang #7923

Last but not least

By the way, welcome to join the RisingWave Slack community. Also check out the good first issue and help wanted issues if you want to join the development of an open source database system!

So much for this week. See you next week (hopefully)! 🤗