Evolution Iceberg supports in-place table evolution . You can evolve a table schema just like SQL — even in nested structures — or change partition layout when data volume chang...
Querying from Google BigQuery Iceberg tables To read an Apache XTable™ (Incubating) synced Iceberg table from BigQuery , you have two options: Using Iceberg JSON metadata file ...
Native implementation Client Side caching is implemented using client tracking listener through RESP3 protocol available in Redis or Valkey. It’s used to speed up read operation...
Source schema Converters Converters available in Gobblin Schema specification Supported data types by different converters Primitive types Complex types Array Map Record En...
Gobblin Execution Modes Overview One important feature of Gobblin is that it can be run on different platforms. Currently, Gobblin can run in standalone mode (which runs on a sing...
Custom Catalog It’s possible to read an iceberg table either from an hdfs path or from a hive table. It’s also possible to use a custom metastore in place of hive. The steps to do...
Introduction Hadoop and S3 The s3a File System The s3 File System Getting Gobblin to Publish to S3 Signing Up For AWS Setting Up EC2 Launching an EC2 Instance EC2 Package I...