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Complete Guide to Data Ingestion: Types, Process, and Best Practices

Databand.ai

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database.

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Last Mile Data Processing with Ray

Pinterest Engineering

Behind the scenes, hundreds of ML engineers iteratively improve a wide range of recommendation engines that power Pinterest, processing petabytes of data and training thousands of models using hundreds of GPUs. In some cases, petabytes of data are streamed into training jobs to train a model.

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

LinkedIn Engineering

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.

Process 119
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Introducing Compute-Compute Separation for Real-Time Analytics

Rockset

When you deconstruct the core database architecture, deep in the heart of it you will find a single component that is performing two distinct competing functions: real-time data ingestion and query serving. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky.

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Open-Sourcing AvroTensorDataset: A Performant TensorFlow Dataset For Processing Avro Data

LinkedIn Engineering

However, we found that many of our workloads were bottlenecked by reading multiple terabytes of input data. To remove this bottleneck, we built AvroTensorDataset , a TensorFlow dataset for reading, parsing, and processing Avro data. If greater than one, records in files are processed in parallel.

Datasets 102
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Stream Rows and Kafka Topics Directly into Snowflake with Snowpipe Streaming

Snowflake

This solution is both scalable and reliable, as we have been able to effortlessly ingest upwards of 1GB/s throughput.” Rather than streaming data from source into cloud object stores then copying it to Snowflake, data is ingested directly into a Snowflake table to reduce architectural complexity and reduce end-to-end latency.

Kafka 126
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Drafting Your Data Pipelines

Team Data Science

I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. With careful consideration and learning about your market, the choices you need to make become narrower and more clear. I'll use Python and Spark because they are the top 2 requested skills in Toronto.