LinkedIn Engineering

OCTOBER 19, 2023

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers. Additionally, they needed the ability to experiment with streaming pipelines in batch mode.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

Data Engineering Podcast

MAY 11, 2020

His most recent endeavor at StreamNative is focused on combining the capabilities of Pulsar with the cloud native movement to make it easier to build and scale real time messaging systems with built in event processing capabilities. And for your machine learning workloads, they’ve got dedicated CPU and GPU instances.

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Lambda Architecture Cloud Kafka Hadoop 100

Knowledge Hut

MAY 2, 2024

Spark also has out of the box support for Machine learning and Graph processing using components called MLlib and GraphX respectively. Machine Learning: MLlib is a Machine Learning library of Spark. MLlib is the Apache Spark’s scalable machine learning library.

Scala 52

Scala Hospitality Healthcare Retail 52

Data Engineering Weekly

MARCH 26, 2023

Contribute to the Rudderstack Transformations Library, Win $1000 RudderStack Transformations lets you customize event data in real time with your own JavaScript or Python code. Now you can win $1,000 cash by contributing a Transformation to our open-source library.

Data Engineering 52

Data Engineering Data Engineer Engineering Lambda Architecture 52

Pinterest Engineering

MAY 2, 2023

So our user sequence real-time indexing pipeline is composed of a Flink job that reads the relevant events as they come into our Kafka streams, fetches the desired features for each event from our feature services, and stores the enriched events into our KV store system. Handles out-of-order inserts.

Lambda Architecture 65

Lambda Architecture Datasets Software Engineer Software Engineering 65

Cloudera

NOVEMBER 2, 2020

Ingest 100s of TB of network event data per day . real-time customer event data alongside CRM data; network sensor data alongside marketing campaign management data). Several billion ad impression events per day are streamed in and stored. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse.

Data Warehouse 91

Data Warehouse Kafka Lambda Architecture Telecommunication 91

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. This architecture shows that simulated sensor data is ingested from MQTT to Kafka.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52