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Revolutionizing Real-Time Streaming Processing: 4 Trillion Events Daily at LinkedIn

LinkedIn Engineering

In 2010, they introduced Apache Kafka , a pivotal Big Data ingestion backbone for LinkedIn’s real-time infrastructure. To transition from batch-oriented processing and respond to Kafka events within minutes or seconds, they built an in-house distributed event streaming framework, Apache Samza. hours to 25 minutes).

Process 119
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Aggregator Leaf Tailer: An Alternative to Lambda Architecture for Real-Time Analytics

Rockset

Aggregator Leaf Tailer (ALT) is the data architecture favored by web-scale companies, like Facebook, LinkedIn, and Google, for its efficiency and scalability. In this blog post, I will describe the Aggregator Leaf Tailer architecture and its advantages for low-latency data processing and analytics.

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Unified Streaming And Batch Pipelines At LinkedIn: Reducing Processing time by 94% with Apache Beam

LinkedIn Engineering

In the past, we often used lambda architecture for processing jobs, meaning that our developers used two different systems for batch and stream processing. In this blog post, we will share our progress, challenges, and lessons learned from implementing Apache Beam. one side is Kafka, the other side is HDFS).

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Deep Dive into Time Series and Event Analytics Specialized RTDW , featuring Apache Druid, Apache Hive, Apache Kafka, and Cloudera DataViz.

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Large-scale User Sequences at Pinterest

Pinterest Engineering

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. To explore life at Pinterest, visit our Careers page.

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What is Data Ingestion? Types, Frameworks, Tools, Use Cases

Knowledge Hut

Lambda architecture: A combination of both batch and real-time processing, the lambda architecture has three layers. The lambda architecture ensures completeness of data with minimal latency. In this blog, we discussed how it benefits business in the long run. It is useful for Big Data ingestion.

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Data Engineering Weekly #124

Data Engineering Weekly

The blog highlights that the job is not just writing SQL but providing a strategic business solution for an organization. The blog is very educative for me about measuring the lifetime value of a customer and segmentation on buying behavior. The BTYD model is excellent for building a recommendation engine and marketing personalization.