stargazers VS Apache ZooKeeper

I used tools (such at this one and this one) to see what other repos our stargazers were starring most frequently. The stargazers of these "other" commonly starred repos became an expanded pool of potential stargazers for Preevy

Spencer Kimball (now CEO at CockroachDB) wrote an interesting article on this topic in 2021 where they created spencerkimball/stargazers based on a Python script. So I started thinking: could I create a data pipeline using Nifi and Kafka (two OSS tools often used with Druid) to get the API data into Druid - and then use SQL to do the analytics? The answer was yes! And I have documented the outcome below. Here’s my analytical pipeline for Github stars data using Nifi, Kafka and Druid.

It's analytics. Google search brings up

https://www.cockroachlabs.com/blog/what-can-we-learn-from-ou...

"Years ago I dedicated a Flex Friday (our version of 20% time) to stargazers, a tool to query the CockroachDB repository for information about its GitHub stars and analyze the results. At the time of writing, we had 6,000+ stars (which felt like a lot), and the data in this blog will be based on that original set of 6,000 stargazers."

Which links to

https://github.com/spencerkimball/stargazers

"GitHub allows visitors to star a repo to bookmark it for later perusal. Stars represent a casual interest in a repo, and when enough of them accumulate, it's natural to wonder what's driving interest. Stargazers attempts to get a handle on who these users are by finding out what else they've starred, which other repositories they've contributed to, and who's following them on GitHub."

Go ahead and use the Stargazers repo yourself to analyze yours (or anyone else’s) repo’s trends. Depending upon the number of Stargazers you have, it can take some time. It took us about 7-8 hours (with a 5K/Hr rate limit).

Apache ZooKeeper — a distributed coordination, synchronization, and configuration service (written in Java);

To use Kafka, we also need to deploy a service that keeps configuration informations such as Zookeeper.

Failure Detection and Recovery It’s not enough to have backup systems. It’s also crucial to detect failures quickly. Modern systems employ monitoring tools and rely on distributed coordination systems such as Zookeeper or etcd to identify faults in real-time: once detected, recovery mechanisms are triggered to restore the service.

zookeeper: is (was?) used for secrets management. it was also used as a basic health check, but has been since been replaced.

You can install Kafka from https://kafka.apache.org/quickstart. Because Druid and Kafka both use Apache Zookeeper, I opted to use the Zookeeper deployment that comes with Druid, so didn’t start it with Kafka. Once running, I created two topics for me to post the data into, and for Druid to ingest from:

Please note that we use Zookeeper as the Governance Center.

Next, review deployment complexity such as DB-less versus database-backed deployments. For example, Kong does require running Cassandra or Postgres. Apigee requires Cassandra, Zookeeper, and Postgres to run, while other solutions like Express Gateway and Tyk only require Redis. Apache APISIX uses etcd as its data store, it stores and manages routing-related and plugin-related configurations in etcd in the Data Plane.

ZooKeeper, a system for coordinating distributed nodes, similar to Google's Chubby

[Unit] Description=Apache Zookeeper server Documentation=http://zookeeper.apache.org Requires=network.target remote-fs.target After=network.target remote-fs.target [Service] Type=simple ExecStart=/usr/local/kafka/bin/zookeeper-server-start.sh /usr/local/kafka/config/zookeeper.properties ExecStop=/usr/local/kafka/bin/zookeeper-server-stop.sh Restart=on-abnormal [Install] WantedBy=multi-user.target

ElasticJob achieves distributed coordination through ZooKeeper. In practical scenarios, users may start multiple jobs in the same project simultaneously, all of which use the same Apache Curator client. There are certain risks due to the nature of ZooKeeper and the callback method of Curator in a single event thread.