Apache ZooKeeper VS Apache Hadoop

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.

Did you check out tools like https://hadoop.apache.org/ ?

check out the various dockerfiles bundled with hadoop on GitHub. you can point to them from within docker-compose. they haven't been updated in a couple years tho.

There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka.

There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS.

A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks.

The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing.

So, clearly with your AP CS class and PLC logic knowledge, if you were dumped into a codebase like Hadoop, QT, or TensorFlow you'd be able to quickly and competently analyze what is going on with that code, understand all the libraries used, know the reasons why certain compromises were made, and be able to make suggestions on how to restructure the code in a different way? Because I've been programming for coming up on two decades and unless a system is within the domains that I have experience in, I would not be able to provide any useful information without a massive onboarding timeline, and definitely wouldn't be able to help redesign anything until actually coding within the system for a significant amount of time.

This requires the use of distributed computation tools such as Spark and Hadoop, Flink and Kafka are used. But for occasional experimentation, Pandas, Geopandas and Dask are some of the commonly used tools.