AWS Big Data

OCTOBER 3, 2023

Systems of this nature generate a huge number of small objects and need attention to compact them to a more optimal size for faster reading, such as 128 MB, 256 MB, or 512 MB. As of this writing, only the optimize-data optimization is supported. For our testing, we generated about 58,176 small objects with total size of 2 GB.

Optimization 110

Optimization Snapshot Data Lake Metadata 110

AWS Big Data

MARCH 2, 2023

Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. At the top of the hierarchy is the metadata file, which stores information about the table’s schema, partition information, and snapshots. Choose Advanced options.

Data Lake 118

Data Lake Data Processing Metadata Snapshot 118

AWS Big Data

NOVEMBER 10, 2023

Your applications can seamlessly read from and write to your Amazon Redshift data warehouse while maintaining optimal performance and transactional consistency. Additionally, you’ll benefit from performance improvements through pushdown optimizations, further enhancing the efficiency of your operations. options(**read_config).option("query",

Data Processing 93

Data Processing Data Lake Data Warehouse Optimization 93

AWS Big Data

JULY 27, 2023

With the launch of Amazon Redshift Serverless and the various deployment options Amazon Redshift provides (such as instance types and cluster sizes), customers are looking for tools that help them determine the most optimal data warehouse configuration to support their Redshift workload.

Testing 66

Testing Data Warehouse Data Processing Snapshot 66

Cloudera

FEBRUARY 8, 2024

Queries containing joins, filters, projections, group-by, or aggregations without group-by can be transparently rewritten by the Hive optimizer to use one or more eligible materialized views. Subsequently, these snapshot IDs are used to determine the delta changes that should be applied to the materialized view rows.

Snapshot 92

Snapshot Metadata Cost-Benefit Data Warehouse 92

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. Update your-iceberg-storage-blog in the following configuration with the bucket that you created to test this example.

Data Lake 85

Data Lake Snapshot Metadata Optimization 85

AWS Big Data

AUGUST 16, 2023

The Iceberg specification allows seamless table evolution such as schema and partition evolution, and its design is optimized for usage on Amazon Simple Storage Service (Amazon S3). On the Code tab, choose Test , then Configure test event. Configure a test event with the default hello-world template event JSON.

Data Lake 72

Data Lake Metadata Testing Snapshot 72