Search Results for "rollback"

...Data engineering best practices using git-like operations on data. lakeFS is an open-source data version control for data lakes. It enables zero-copy Dev / Test isolated environments, continuous quality validation, atomic rollback on bad data, reproducibility, and more. Data is dynamic, it changes over time. Dealing with that without a data version control system is error-prone and labor-intensive. With lakeFS, your data lake is version controlled and you can easily time-travel between consistent snapshots of the lake. Easier ETL testing - test your ETLs on top of production data, in isolation, without copying anything. ...

Apache Hudi (pronounced Hoodie) stands for Hadoop Upserts Deletes and Incrementals. Hudi manages the storage of large analytical datasets on DFS (Cloud stores, HDFS or any Hadoop FileSystem compatible storage). Apache Hudi is a transactional data lake platform that brings database and data warehouse capabilities to the data lake. Hudi reimagines slow old-school batch data processing with a powerful new incremental processing framework for low latency minute-level analytics. Hudi provides...

The q utility is a platform for creating and managing data analysis pipelines. It expands the value of your existing job scheduler - either Grid Engine or TORQUE PBS - through numerous functions that help you organize, submit, monitor, manage and share your informatics work. Data processing pipelines require high-level organization and parallelization of work to optimize resource utilization and decrease the time to results. q (from queue) allows complex job sequences to be efficiently...

...Its a very simple and straightforward way to bridge the gap between in-memory data structures and long-term storage. It has the convenience of Java SDK TreeMap and TreeSet classes and is used the same easy way, but it includes rollback through undo logging to checkpoint data so it does not wind up in an unknown state regardless of failures. Data storage in the exabyte range is possible using filesystem and/or memory-mapped IO. Three levels of configurable write-through caching at different granularities ensure performance.