Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 5 days ago

I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 25 days ago

You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 1 month ago

Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 2 months ago

Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 4 months ago

Somebody else pointed out RescueTime, but if keeping it local is a priority, I recommend Qbserve, which I've been using (mostly passively in the background) for a few years now. [0] https://qotoqot.com/qbserve/. - Source: Hacker News / 6 months ago

One of the hardest things for me about grad school (that I'm still struggling with!) is figuring out how to schedule my own day when I have few external things keeping my day in shape for me. it's been really helpful just to have the data of how much time I usually spend on things/what I've done that day... I can see where all my time is going lmao and readjust as needed. I use toggl track in conjunction with... Source: 6 months ago

Is https://qotoqot.com/qbserve/ actually doing this ? I can't seem to figure out if it tracks individual files inside apps. Source: over 1 year ago

An unconventional, and somewhat uncomfortable bit of discipline: I used Qbserve (for mac), which is an automatic time tracker. I taught it which websites were productive (/r/LaTeX, StackExchange, and ArXiV.org) and which were not (/r/GradSchool etc lol). It notified me when I was spending too much time not being productive, and also notified me when I had done "enough". Source: over 1 year ago

I use Qbserve [1] after seeing it mentioned in a previous thread. Really helpful for seeing where time was spent over the course of the day/week. Collected data all stored locally too [1] https://qotoqot.com/qbserve/. - Source: Hacker News / about 2 years ago