Scalable Data Analytics With Azure Data — Explorer Read Online [repack]

We’ve been sold a comforting lie for the last decade.

Scalability is not about how much data you can store . It’s about how much data you can forget —while still answering the question. scalable data analytics with azure data explorer read online

If you haven't spent a weekend ingesting a billion log lines into ADX and running a summarize across them in under two seconds, you haven't yet understood what "scalable" actually means. We’ve been sold a comforting lie for the last decade

Spark shuffles are the enemy of scalability. ADX uses a concept called extents (immutable compressed column segments). When you scale out, ADX doesn't reshuffle the world. It redistributes the metadata about those extents. The data stays put; the query logic moves to the data. This is why a single ADX cluster can handle 200 MB/s of sustained ingestion and still serve interactive queries. If you haven't spent a weekend ingesting a

Azure Data Explorer succeeds because it indexes aggressively at ingest so it can ignore aggressively at query. When you "read online" in ADX, you aren't reading the data. You are reading the index of the index .