Remove Big Data Remove Data Processing Remove Metadata
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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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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",

Data Lake 105
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

An extract, transform, and load (ETL) process using AWS Glue is triggered once a day to extract the required data and transform it into the required format and quality, following the data product principle of data mesh architectures. From here, the metadata is published to Amazon DataZone by using AWS Glue Data Catalog.

IoT 111
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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

This approach simplifies your data journey and helps you meet your security requirements. The SageMaker Lakehouse data connection testing capability boosts your confidence in established connections. On your project, in the navigation pane, choose Data. For Add data source , choose Add connection. Choose the plus sign.

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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

The IAM role ARN must be the same for both the OpenSearch Servicer sink definition and the Kinesis Data Streams source definition. You can control what data gets indexed in different indexes using the index definition in the sink.

Metadata 122
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How BMW streamlined data access using AWS Lake Formation fine-grained access control

AWS Big Data

To achieve this, they aimed to break down data silos and centralize data from various business units and countries into the BMW Cloud Data Hub (CDH). Consumer accounts : Used by data consumers to implement use cases insights and build applications tailored to their business needs.

Data Lake 109
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Reduce your compute costs for stream processing applications with Kinesis Client Library 3.0

AWS Big Data

Load balancing challenges with operating custom stream processing applications Customers processing real-time data streams typically use multiple compute hosts such as Amazon Elastic Compute Cloud (Amazon EC2) to handle the high throughput in parallel. KCL uses DynamoDB to store metadata such as shard-worker mapping and checkpoints.