AWS Glue Data Catalog

5 minutes 5 Questions

The AWS Glue Data Catalog is a fully managed, Hive-compatible, and Apache Spark compatible metadata repository that enables users to store, discover, query, and manage their data. It integrates with data stores like Amazon S3, Amazon Redshift, and Amazon RDS. The Data Catalog stores metadata about the datasets and allows you to utilize this metadata in ETL jobs or data analytics. The searchable, centralized repository allows for faster data discovery and collaboration between data scientists and engineers while maintaining a reliable and consistent view of your data.

Guide to AWS Glue Data Catalog

AWS Glue Data Catalog serves as a centralized metadata repository for your data stores in AWS. It stores metadata related to data sources, transformations, and targets.

Why is it important:
The AWS Glue Data Catalog is an essential part of the AWS ecosystem because it simplifies the process of data discovery and data schema management. By centralizing metadata across a wide variety of data sources, it can drive the efficiency of big data, analytics, and machine learning tasks.

What it is:
The Glue Data Catalog is a persistent metadata store in AWS Glue that provides a unified view of your data lake. It stores structural information about your data such as table definition, schema, and partition metadata, and can be used as a metastore for services like AWS Athena, EMR, and Redshift Spectrum.

How it works:
Data Catalog associates metadata with unique identifiers(catalog ID, database name, and table name). It makes use of crawlers to extract metadata from various sources and store it in an Apache Hive Metastore compatible format. This data can then be discovered and queried directly.

Exam Tips: Answering Questions on AWS Glue Data Catalog
1. Understand the role of AWS Glue Data Catalog: It acts as a centralized metadata repository. Be familiar with its functions in data discovery and metadata management.
2. Know the components: The main components include Tables, Databases, Crawlers, and Classifiers.
3. Understand Crawlers: Crawlers in AWS Glue Data Catalog retrieve metadata from data stores, identify data formats, and suggest schemas. A common question type might involve understanding what happens when a Crawler runs.
4. Be aware of compatibility: The Data Catalog is compatible with an Apache Hive Metastore. This interplay might come up in exam questions involving multiple AWS services.

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