Remove Metadata Remove Recreation/Entertainment Remove Snapshot
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Accelerate your migration to Amazon OpenSearch Service with Reindexing-from-Snapshot

AWS Big Data

In this post, we will introduce a new mechanism called Reindexing-from-Snapshot (RFS), and explain how it can address your concerns and simplify migrating to OpenSearch. Documents are parsed from the snapshot and then reindexed to the target cluster, so that performance impact to the source clusters is minimized during migration.

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Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

AWS Big Data

However, altering schema and table partitions in traditional data lakes can be a disruptive and time-consuming task, requiring renaming or recreating entire tables and reprocessing large datasets. Apache Iceberg manages these schema changes in a backward-compatible way through its innovative metadata table evolution architecture.

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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

This means the data files in the data lake aren’t modified during the migration and all Apache Iceberg metadata files (manifests, manifest files, and table metadata files) are generated outside the purview of the data. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files.

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Implement disaster recovery with Amazon Redshift

AWS Big Data

With built-in features such as automated snapshots and cross-Region replication, you can enhance your disaster resilience with Amazon Redshift. To develop your disaster recovery plan, you should complete the following tasks: Define your recovery objectives for downtime and data loss (RTO and RPO) for data and metadata.

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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

Iceberg doesn’t optimize file sizes or run automatic table services (for example, compaction or clustering) when writing, so streaming ingestion will create many small data and metadata files. Offers different query types , allowing to prioritize data freshness (Snapshot Query) or read performance (Read Optimized Query).

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5 Reasons to Use Apache Iceberg on Cloudera Data Platform (CDP)

Cloudera

The table information (such as schema, partition) is stored as part of the metadata (manifest) file separately, making it easier for applications to quickly integrate with the tables and the storage formats of their choice. Iceberg, on the other hand, is an open table format that works with open file formats to avoid this coupling.

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Apache HBase online migration to Amazon EMR

AWS Big Data

And during HBase migration, you can export the snapshot files to S3 and use them for recovery. Additionally, we deep dive into some key challenges faced during migrations, such as: Using HBase snapshots to implement initial migration and HBase replication for real-time data migration.

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