Apache Flink Reviews

MIT App Inventor Reviews

Apache Flink mentions (30)

• Show HN: Restate, low-latency durable workflows for JavaScript/Java, in Rust

  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 / 24 days ago

• Array Expansion in Flink SQL

  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 / about 1 month ago

• Show HN: An SQS Alternative on Postgres

  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 2 months ago

• Top 10 Common Data Engineers and Scientists Pain Points in 2024

  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 / 3 months ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  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 / 5 months ago

MIT App Inventor mentions (40)

• Looking for savable graphing methods

  First thought, play with MIT App Inventor https://appinventor.mit.edu/, they have dedicated blocks for graphing and cross-platform implementations of Bluetooth for Android and iOS. The data format is still up to you. Source: about 1 year ago

• App for recording time periods

  Or you could go to https://appinventor.mit.edu/ and design your own custom app (no widget, though). Source: about 1 year ago

• Easiest code to learn to make an app?

  If you want to make a mobile app you could try https://appinventor.mit.edu/. Source: about 1 year ago

• Trying to have a Ubuntu server I can turn on from my phone, log in as user, and start the Docker containers for my server. How do I automate this process?

  Maybe a raspberry pi that's on 24/7 connected to wifi and use that to send the wake over lan signal to the server? Arduino on the power pins also works, I did something quite similar but with a Bluetooth board, the code was really simple I just made an Android app with MIT app inventor that sent a signal to the hc_05 bt board, once the Arduino received that signal it shorted the power pin to 5v for half a second... Source: over 1 year ago

• Am searching for a partner who can help me with an app idea

  If your idea isn't complicated, have a look at MIT App Inventor. It literally is, drag-and-drop. That should get you started. Source: over 1 year ago