Remove 2022 Remove Analytics Remove Data Transformation Remove Snapshot
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How to Use Apache Iceberg in CDP’s Open Lakehouse

Cloudera

In June 2022, Cloudera announced the general availability of Apache Iceberg in the Cloudera Data Platform (CDP). The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ).

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Cloudera Data Engineering 2021 Year End Review

Cloudera

Today it’s used by many innovative technology companies at petabyte scale, allowing them to easily evolve schemas, create snapshots for time travel style queries, and perform row level updates and deletes for ACID compliance. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. .

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Perform upserts in a data lake using Amazon Athena and Apache Iceberg

AWS Big Data

Apache Iceberg is an open table format for data lakes that manages large collections of files as tables. It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. Create a table to point to the CDC data. Upload 20220922-184314489.csv

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Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

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Build and manage your modern data stack using dbt and AWS Glue through dbt-glue, the new “trusted” dbt adapter

AWS Big Data

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

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