petermarshallio commented on code in PR #14523:
URL: https://github.com/apache/druid/pull/14523#discussion_r1257879545
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examples/quickstart/jupyter-notebooks/notebooks/03-query/03-approxCountDistinct.ipynb:
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@@ -0,0 +1,470 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "557e06e8-9b35-4b34-8322-8a8ede6de709",
+ "metadata": {},
+ "source": [
+ "# Counting distinct values\n",
+ "\n",
+ "__It's extremely common for analysts to want to count unique occurences
of some dimension value in data. With the Druid database's history of large
volumes of data comes an advanced computer science technique to speed up this
calculation through approximation. In this tutorial, work through some examples
and see the effect of turning it on and off, and of making it even faster by
pre-generating the objects that Druid uses to execute the query.__\n",
Review Comment:
Habit as a blog intro. Removed the boldness.
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