Bytes Java Kafka 
Confluent
JULY 24, 2019
Using Jaeger tracing, I’ve been able to answer an important question that nearly every Apache Kafka ® project that I’ve worked on posed: how is data flowing through my distributed system? Distributed tracing with Apache Kafka and Jaeger. Example of a Kafka project with Jaeger tracing. What does this all mean?
Confluent
FEBRUARY 12, 2019
One of the most common integrations that people want to do with Apache Kafka ® is getting data in from a database. The existing data in a database, and any changes to that data, can be streamed into a Kafka topic. Here, I’m going to dig into one of the options available—the JDBC connector for Kafka Connect. Introduction.
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Confluent
OCTOBER 24, 2019
I’ve written an event sourcing bank simulation in Clojure (a lisp build for Java virtual machines or JVMs) called open-bank-mark , which you are welcome to read about in my previous blog post explaining the story behind this open source example. The schemas are also useful for generating specific Java classes. The bank application.
Confluent
JULY 10, 2019
As discussed in part 2, I created a GitHub repository with Docker Compose functionality for starting a Kafka and Confluent Platform environment, as well as the code samples mentioned below. We used Groovy instead of Java to write our UDFs, so we’ve applied the groovy plugin. jar Zip file size: 5849 bytes, number of entries: 5.
Confluent
MAY 29, 2019
In part 1 , we discussed an event streaming architecture that we implemented for a customer using Apache Kafka ® , KSQL from Confluent, and Kafka Streams. In part 3, we’ll explore using Gradle to build and deploy KSQL user-defined functions (UDFs) and Kafka Streams microservices. gradlew composeUp. The KSQL pipeline flow.
ProjectPro
JULY 26, 2016
Hiring managers agree that “Java is one of the most in-demand and essential skill for Hadoop jobs. But how do you get one of those hot java hadoop jobs ? You have to ace those pesky java hadoop job interviews artfully. To demonstrate your java and hadoop skills at an interview, preparation is vital.
Pinterest Engineering
NOVEMBER 28, 2023
When there is a full GC, it leads to full halt to the data processing pipeline and causes both back-pressure for upstream kafka clusters and cascading failure for downstream TSDB. Pyoung = Seden / Ralloc where Pyoung is the period between young GC, Seden is the size of Eden and Ralloc is the rate of memory allocations (bytes per second).
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