Скачать или смотреть Day 54: Implement a Query Language for Complex Log Searches

In this lesson, you build a production-grade, SQL-like query language that allows users to search and analyze distributed logs intuitively. You implement a full query pipeline—parsing and validating queries, pushing execution down to distributed index nodes, optimizing execution plans, and efficiently aggregating results. The system supports familiar constructs like filtering, grouping, sorting, and aggregations while operating across a sharded log index.

This matters because indexes alone don’t create value—queries do. At scale, poorly designed query engines overwhelm networks and time out under load. Production systems solve this by pushing computation to where data lives, minimizing data movement, and merging results incrementally. This lesson teaches the same core patterns used by Elasticsearch, Splunk, and BigQuery to deliver sub-second analytics over massive datasets.

#LogSearch #QueryEngines #DistributedSystems #SystemDesign #Observability #BigData