This is an automated email from the ASF dual-hosted git repository.
git-site-role pushed a commit to branch asf-site
in repository
https://gitbox.apache.org/repos/asf/incubator-datasketches-website.git
The following commit(s) were added to refs/heads/asf-site by this push:
new e19b1d0 Automatic Site Publish by Buildbot
e19b1d0 is described below
commit e19b1d0ff9eb511f1b24d8b0b85427101fe3710f
Author: buildbot <[email protected]>
AuthorDate: Wed May 27 05:16:39 2020 +0000
Automatic Site Publish by Buildbot
---
output/docs/Community/KDD_Tutorial_Summary.html | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/output/docs/Community/KDD_Tutorial_Summary.html
b/output/docs/Community/KDD_Tutorial_Summary.html
index 1d5c504..b02c77f 100644
--- a/output/docs/Community/KDD_Tutorial_Summary.html
+++ b/output/docs/Community/KDD_Tutorial_Summary.html
@@ -63,7 +63,7 @@
<p>Speed, cost, and scale. These are 3 of the biggest challenges in analyzing
big data. While modern data systems continue to push the boundaries of scale,
the problems of speed and cost are fundamentally tied to the size of data being
scanned or processed. Processing thousands of queries that each access
terabytes of data with sub-second latency remains infeasible. Data sketching
techniques provide means to drastically reduce this size, allowing for
real-time or interactive data analysi [...]
-<p>This tutorial covers a number of useful data sketching and sampling methods
and demonstrate their use using the Apache DataSketches project. We focus
particularly on common analytic problems such as counting distinct items,
quantiles, histograms, heavy hitters, and aggregations with large group-bys.
For these, we covers algorithms, techniques, and theory that can aid both
practitioners and theorists in constructing sketches and designing systems that
achieve desired error guarantees. [...]
+<p>This tutorial covers a number of useful data sketching and sampling methods
and demonstrate their use using the Apache DataSketches project[3]. We focus
particularly on common analytic problems such as counting distinct items,
quantiles, histograms, heavy hitters, and aggregations with large group-bys.
For these, we covers algorithms, techniques, and theory that can aid both
practitioners and theorists in constructing sketches and designing systems that
achieve desired error guarantee [...]
<h2 id="audience">Audience</h2>
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
