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Accelerate your migration to Amazon OpenSearch Service with Reindexing-from-Snapshot

AWS Big Data

Each Lucene index (and, therefore, each OpenSearch shard) represents a completely independent search and storage capability hosted on a single machine. As a backup strategy, snapshots can be created automatically in OpenSearch, or users can create a snapshot manually for restoring it on to a different domain or for data migration.

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Disaster recovery strategies for Amazon MWAA – Part 2

AWS Big Data

In particular, we discussed two key strategies: backup and restore and warm standby. In this post, we dive deep into the implementation for both strategies and provide a deployable solution to realize the architectures in your own AWS account. The solution for this post is hosted on GitHub. The steps are as follows: [1.a]

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Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

format(dbname, table_name)) except Exception as ex: print(ex) failed_table = {"table_name": table_name, "Reason": ex} unprocessed_tables.append(failed_table) def get_table_key(host, port, username, password, dbname): jdbc_url = "jdbc:sqlserver://{0}:{1};databaseName={2}".format(host, To start the job, choose Run. format(dbname)).config("spark.sql.catalog.glue_catalog.catalog-impl",

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Use Amazon Kinesis Data Streams to deliver real-time data to Amazon OpenSearch Service domains with Amazon OpenSearch Ingestion

AWS Big Data

For example, you can use metadata about the Kinesis data stream name to index by data stream ( ${getMetadata("kinesis_stream_name") ), or you can use document fields to index data depending on the CloudWatch log group or other document data ( ${path/to/field/in/document} ).

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How BMW streamlined data access using AWS Lake Formation fine-grained access control

AWS Big Data

The CDH is used to create, discover, and consume data products through a central metadata catalog, while enforcing permission policies and tightly integrating data engineering, analytics, and machine learning services to streamline the user journey from data to insight.

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What you need to know about product management for AI

O'Reilly on Data

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. AI product estimation strategies. You might have millions of short videos , with user ratings and limited metadata about the creators or content.

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Amazon OpenSearch Service Under the Hood : OpenSearch Optimized Instances(OR1)

AWS Big Data

The following diagram illustrates an indexing flow involving a metadata update in OR1 During indexing operations, individual documents are indexed into Lucene and also appended to a write-ahead log also known as a translog. In the event of an infrastructure failure, an OpenSearch domain can end up losing one or more nodes.