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Streaming Big Data Files from Cloud Storage

Towards Data Science

This continues a series of posts on the topic of efficient ingestion of data from the cloud (e.g., Before we get started, let’s be clear…when using cloud storage, it is usually not recommended to work with files that are particularly large. There a number of methods for downloading a file to a local disk.

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Creating a Data Pipeline with Spark, Google Cloud Storage and Big Query

Towards Data Science

And that’s the target of today’s post — We’ll be developing a data pipeline using Apache Spark, Google Cloud Storage, and Google Big Query (using the free tier) not sponsored. Google Cloud Storage (GCS) is Google’s blob storage. Setting up the environment All the code is available on this GitHub repository.

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Modern Data Engineering: Free Spark to Snowpark Migration Accelerator for Faster, Cheaper Pipelines in Snowflake

Snowflake

With familiar DataFrame-style programming and custom code execution, Snowpark lets teams process their data in Snowflake using Python and other programming languages by automatically handling scaling and performance tuning. It provided us insights as to code compatibility and allowed us to better estimate our migration time.”

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Introducing rules_gcs

Tweag

We recently completed a project with IMAX, where we learned that they had developed a way to simplify and optimize the process of integrating Google Cloud Storage (GCS) with Bazel. rules_gcs is a Bazel ruleset that facilitates the downloading of files from Google Cloud Storage. What is rules_gcs ?

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Introducing Compute-Compute Separation for Real-Time Analytics

Rockset

Back when I used to work at facebook, my team, led by amazing builders such as Dhruba Borthakur and Igor Canadi (who also happen to be the co-founder and founding architect at Rockset), forked the LevelDB code base and turned it into RocksDB, an embedded database optimized for server-side storage.

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Top 10 Data Science Websites to learn More

Knowledge Hut

File systems can store small datasets, while computer clusters or cloud storage keeps larger datasets. The designer must decide and understand the data storage, and inter-relation of data elements. All these datasets are totally free to download off Kaggle.

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Aaand the New NiFi Champion is…

Cloudera

RK built some simple flows to pull streaming data into Google Cloud Storage and Snowflake. Many developers use DataFlow to filter/enrich streams and ingest into cloud data lakes and warehouses where the ability to process and route anywhere makes DataFlow very effective. Congratulations Vince!