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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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Netflix Cloud Packaging in the Terabyte Era

Netflix Tech

From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step. Uploading and downloading data always come with a penalty, namely latency.

Cloud 96
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Modern Data Engineering: Free Spark to Snowpark Migration Accelerator for Faster, Cheaper Pipelines in Snowflake

Snowflake

Ingestion Pipelines : Handling data from cloud storage and dealing with different formats can be efficiently managed with the accelerator. Get started The Snowpark Migration Accelerator is available now for free just by downloading the installer onto your local machine or container.

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Processing medical images at scale on the cloud

Tweag

Thankfully, cloud-based infrastructure is now an established solution which can help do this in a cost-effective way. As a simple solution, files can be stored on cloud storage services, such as Azure Blob Storage or AWS S3, which can scale more easily than on-premises infrastructure. But as it turns out, we can’t use it.

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HDFS Data Encryption at Rest on Cloudera Data Platform

Cloudera

Install KTS using parcels (it requires parcels to be downloaded from archive.cloudera.com, and configure into CM). Parcels Configuration for KTS: Download the parcels for KTS as they are not part of the CDP parcels. sent 11,286 bytes received 172 bytes 2,546.22 Once KTS is in place with one of the above two choices, .

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Deploying Kafka Streams and KSQL with Gradle – Part 2: Managing KSQL Implementations

Confluent

Of course, a local Maven repository is not fit for real environments, but Gradle supports all major Maven repository servers, as well as AWS S3 and Google Cloud Storage as Maven artifact repositories. zip Zip file size: 3593 bytes, number of entries: 9 drwxr-xr-x 2.0 6 objects dropped. 6 objects created. m2 directory.

Kafka 96
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Deploying Kafka Streams and KSQL with Gradle – Part 3: KSQL User-Defined Functions and Kafka Streams

Confluent

jar Zip file size: 5849 bytes, number of entries: 5. jar Zip file size: 11405084 bytes, number of entries: 7422. It can then send that activity to cloud services like AWS Kinesis, Amazon S3, Cloud Pub/Sub, or Google Cloud Storage and a few JDBC sources. jar Archive: functions/build/libs/functions-1.0.0.jar

Kafka 89