Velociraptor – The Next Generation of RaptorX – Vladimir Rodionov, Carrot Cache

Velociraptor – The Next Generation of RaptorX – Vladimir Rodionov, Carrot Cache

Vladimir Rodionov, founder of Carrot Cache will present the Velociraptor – the next evolution of PrestoDB hierarchical caching framework RaptorX. Velociraptor enables efficient data and meta-data caching well beyond RaptorX limits in terms of number of data files (multi-billions), number of table partitions (multi-millions) and number of table columns (multi-thousands). Velociraptor replaces all five RaptorX caches (Hive meta-data, file list, query result fragments, ORC/Parquet meta-data and data I/O) with a scalable solution, based on Carrot Cache, which does not pollute JVM heap memory, does not affect Java Garbage Collector, keeps all data and meta-data off Java heap memory or on disk and can scale well beyond server’s physical RAM limit. Velociraptor supports server restart, by quickly saving and loading data to/from disk for automatic cache warm up.

A Git-like Repository for your Data Lake – Vinodhini Sivakami Duraisamy, Treeverse

A Git-like Repository for your Data Lake – Vinodhini Sivakami Duraisamy, Treeverse

A Git-like Repository for your Data Lake – Vinodhini Sivakami Duraisamy, Treeverse We tend to adopt practices that improve the flexibility of development and the velocity of code deployment, but how confident are we that the complex data system is safe once it arrives in production? We must be able to experiment in production and automate actions while minimizing customer pain and reducing damage to code and data. If your product’s value is derived from data in the shape of analytics or machine learning, losing it, or having corrupted data, can easily translate into pain. In this session, you will discover how chaos engineering principles apply to distributed data systems and the tools that enable us to make our data workloads more resilient. 

After RaptorX: Improve Performance Understanding and Workload Analysis in Presto – Ke Wang & Bin Fan

After RaptorX: Improve Performance Understanding and Workload Analysis in Presto – Ke Wang & Bin Fan

RaptorX, an umbrella project presented in PrestoCon Day in March, enabled the Presto interactive fleet in Facebook to reduce latency by 10x, based on a set of architectural improvements and optimizations with hierarchical caching. This presentation provides an update on the follow-up enhancement. Bin Fan from Alluxio will talk about the exploration of a probabilistic algorithm in Alluxio caching to estimate cache working set and the implementation of shadow cache Ke Wang from Facebook will talk about how shadow cache is used to understand the system bottleneck for better resource allocation and query routing decisions. She will also cover a recent improvement in collecting and aggregating per-query runtime statistics on the Presto engine to better understand the time breakdown, resource usage breakdown and cache hit rate on a per-query basis, which can help identify areas of improvement.

RaptorX: Building a 10X Faster Presto – James Sun, Facebook, Inc

RaptorX: Building a 10X Faster Presto – James Sun, Facebook, Inc

RaptorX is an internal project name aiming to boost query latency significantly beyond what vanilla Presto is capable of. For this session, we introduce the hierarchical cache work including Alluxio data cache, fragment result cache, etc. Cache is the key building block for RaptorX. With the support of the cache, we are able to boost query performance by 10X. This new architecture can beat performance oriented connectors like Raptor with the added benefit of continuing to work with disaggregated storage.