Remove 2022 Remove Data Warehouse Remove Snapshot Remove Testing
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Enable Multi-AZ deployments for your Amazon Redshift data warehouse

AWS Big Data

Originally published on December 9th, 2022. Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Amazon Redshift is a cloud-based data warehouse that supports many recovery capabilities to address unforeseen outages and minimize downtime.

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Open Data Lakehouse powered by Iceberg for all your Data Warehouse needs

Cloudera

Cloudera Contributors: Ayush Saxena, Tamas Mate, Simhadri Govindappa Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), we are excited to see customers testing their analytic workloads on Iceberg. We will publish follow up blogs for other data services. ID, TBL_ICEBERG_PART_2.NAME,

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

AWS Big Data

It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. Athena also supports the ability to create views and perform VACUUM (snapshot expiration) on Apache Iceberg tables to optimize storage and performance. Create a table to point to the CDC data.

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

In early 2022, AWS announced general availability of Athena ACID transactions, powered by Apache Iceberg. Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. The snapshot points to the manifest list.

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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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Join a streaming data source with CDC data for real-time serverless data analytics using AWS Glue, AWS DMS, and Amazon DynamoDB

AWS Big Data

Under Instance configuration , for High Availability , choose Dev or test workload (Single-AZ). Create a Python file called generate-data-for-kds.py : $ python3 generate-data-for-kds.py client("kinesis")) This script puts a Kinesis data stream record every 2 seconds. Choose Create replication instance. mode("append").save(s3_output_folder)