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Write Optimized Spark Code for Big Data Applications

DZone

Apache Spark is a powerful open-source distributed computing framework that provides a variety of APIs to support big data processing. PySpark is the Python API for Apache Spark , which allows Python developers to write Spark applications using Python instead of Scala or Java.

Big Data 173
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Kubernetes in the wild report 2023

Dynatrace

Java, Go, and Node.js Big data : To store, search, and analyze large datasets, 32% of organizations use Elasticsearch. Java, Go, and Node.js Java Virtual Machine (JVM)-based languages are predominant. Java Virtual Machine (JVM)-based languages are predominant. Kubernetes moved to the cloud in 2022.

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Big / Bug Data: Analyzing the Apache Flink Source Code

DZone

Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. It is an open-source framework for distributed processing of large amounts of data.

Code 159
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A guide to Autonomous Performance Optimization

Dynatrace

If you want to see a more hands-on approach, I encourage you to watch the recording as Stefano did a live demo of Akamas’s integration with Dynatrace, showing how to minimize the footprint of a Java application with automated JVM tuning. Q4: Do you have a way to integrate new technology stacks to Akamas via a plugin mechanism?

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Data Movement in Netflix Studio via Data Mesh

The Netflix TechBlog

As of now, CDC sources have been implemented for data stores at Netflix (MySQL, Postgres). CDC events can also be sent to Data Mesh via a Java Client Producer Library. The Studio Tech Solutions team provides near real-time reports in some data tool of choice, which we call trackers to empower the decision making.

Big Data 255
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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 207
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Comparing Apache Ignite In-Memory Cache Performance With Hazelcast In-Memory Cache and Java Native Hashmap

DZone

This article compares different options for the in-memory maps and their performances in order for an application to move away from traditional RDBMS tables for frequently accessed data.

Cache 147