Remove Cost-Benefit Remove Metadata Remove Snapshot Remove Webinar
article thumbnail

Materialized Views in Hive for Iceberg Table Format

Cloudera

The snapshotId of the source tables involved in the materialized view are also maintained in the metadata. Subsequently, these snapshot IDs are used to determine the delta changes that should be applied to the materialized view rows. Furthermore, it is partitioned on the d_year column.

article thumbnail

Optimization Strategies for Iceberg Tables

Cloudera

It offers several benefits such as schema evolution, hidden partitioning, time travel, and more that improve the productivity of data engineers and data analysts. Problem with too many snapshots Everytime a write operation occurs on an Iceberg table, a new snapshot is created. See Write properties.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

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

Cloudera

Every table change creates an Iceberg snapshot, this helps to resolve concurrency issues and allows readers to scan a stable table state every time. The table metadata is stored next to the data files under a metadata directory, which allows multiple engines to use the same table simultaneously.

article thumbnail

From Hive Tables to Iceberg Tables: Hassle-Free

Cloudera

However, as there are already 25 million terabytes of data stored in the Hive table format, migrating existing tables in the Hive table format into the Iceberg table format is necessary for performance and cost. They also provide a “ snapshot” procedure that creates an Iceberg table with a different name with the same underlying data.

article thumbnail

Announcing Trial and Domino 3.5: Control Center for Data Science Leaders

Domino Data Lab

On the flip side, when data scientists mark a project as complete with a description of the project conclusion, Domino also captures this metadata for project tracking and future references. All of this metadata captured can be useful for organizational learning, organize projects and help to avoid similar issues in the future. .