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Conviva built a high-performance streaming analytics pipeline processing trillions of events daily—then made it programmable for diverse workloads. This talk covers how they boosted throughput & memory efficiency 5x+ with Rust, zero-copy data, better execution models & smarter data structures.
Evan has been a distributed systems / data / software engineer for twenty years. He led a team developing FiloDB, an open source (github.com/filodb/FiloDB) distributed time series database that can process a million records per second PER NODE and simultaneously answer a large number of concurrent queries per second. FiloDB is the production telemetry DB at Apple. He has architected, developed, and productionized large scale data and telemetry systems at companies including Apple, and loves solving the most challenging technical problems at both large and small scales, from advanced custom data structures to distributed coordination. He is an expert in bleeding edge #jvm #java #scala and #rust performance. Current interests include Rust and columnar compression. He has led the design and implementation of multiple big data platforms based on Rust, Apache Storm, Spark, Kafka, Cassandra, and Scala/Akka. He has been an active contributor to the Apache Spark project, and a two-time Datastax Cassandra MVP.
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