LinkedIn Reviews

1. Bozidar

   over 1 year ago

   Great website for professional network, started using it recently and already found some business partners and a couple of job opportunities.

   👍 Pros:    Networking

Apache Flink Reviews

LinkedIn mentions (120)

• A Day In My Dev Life

  To end with a positive note. I’m so happy I started this journey of writing about my day. I’ve always liked documenting my journey in different ways but I feel like I finally found something I can maintain. I tried all kinds of strategies on Instagram, TikTok and YouTube but never kept to one, despite all the systems I tried building for it. I’d like to thank you, my dear reader. I don’t know if you come from... - Source: dev.to / 26 days ago

• How good is https://www.virustotal.com/ to scan an apk?

  The reports seem detailed. I liked the interesting links - interesting to see why we have social media links like linkedin.com in a game app. Source: 6 months ago

• Tell HN: LinkedIn has one of the worst dark patterns I have seen on the web

  xdg-open https://linkedin.com. - Source: Hacker News / 7 months ago

• Are there any ReactJs Job left?

  2 YOE, Front end developer with 4 Freelance live projects. My current company (remote) is going be bankcrupt, as they have embraced crypto. I don't want to be in a sinking ship. I am trying to switch for past 2 months only 3 interview so far. I have been applying from naukri.com indeed.com linkedin.com hirist.com anglelist no one is freaking wants Front end developer. I am depressed AF, get up work for some... Source: 10 months ago

• Career change questions

  I just looked on linkedin.com Avelo airlines had opening, but, it showed 20 people were applying. Source: 12 months ago

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 / 5 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 / 25 days 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 1 month 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 / 2 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 / 4 months ago