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Lakesail rewrote Apache Spark in Rust, removing the JVM layer. The new implementation runs eight times faster and cuts infrastructure costs by 94%.
- Rewrote Apache Spark's core in Rust (~200,000 lines), eliminating the JVM entirely while keeping familiar Spark APIs
- Claims ~8x throughput improvement on standard analytics workloads by avoiding GC pauses and Java bytecode overhead
- Reports ~94% cost reduction on AWS C5 instances running identical TPC-DS queries, due to lower CPU/memory use
- Core engine is open source (Apache 2.0) and called production-ready, though advanced Spark SQL window functions and some MLlib algorithms are still missing
This article presents jsongrep, a tool for querying JSON documents efficiently using a DFA-based approach. It explains the tool's features, how it processes queries, and benchmarks its performance against other JSON querying tools.
- jsongrep compiles queries into a DFA upfront instead of interpreting them, giving single-pass, constant-time-per-symbol matching versus tools that backtrack or revisit nodes
- It benchmarks faster than jq, jmespath, jsonpath-rust, and jql
- It's a focused search tool (paths, wildcards, recursive descent, filtering), not a transformation tool like jq, and still lacks some of jq's broader functionality