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new 4a545ee5 update KeyFeatures
4a545ee5 is described below
commit 4a545ee5772ba146d8efd3c7d6deeb57764d98aa
Author: Lee Rhodes <[email protected]>
AuthorDate: Sat Dec 6 16:51:28 2025 -0800
update KeyFeatures
---
docs/Architecture/KeyFeatures.md | 35 ++++++++++++++++++++++-------------
1 file changed, 22 insertions(+), 13 deletions(-)
diff --git a/docs/Architecture/KeyFeatures.md b/docs/Architecture/KeyFeatures.md
index f6477789..792eb287 100644
--- a/docs/Architecture/KeyFeatures.md
+++ b/docs/Architecture/KeyFeatures.md
@@ -30,23 +30,25 @@ layout: doc_page
configurable by trading off sketch size with accuracy.
* Designed for <a
href="{{site.docs_dir}}/Architecture/LargeScale.html">Large-scale</a> computing
environments
that must handle <b>Big Data</b>, e.g.:
- * [Hadoop](https://hadoop.apache.org/)
- * [Pig](https://pig.apache.org)
- * [Hive](https://hive.apache.org)
+ *
[Google/BigQuery](https://cloud.google.com/blog/products/data-analytics/bigquery-supports-apache-datasketches-for-approximate-analytics)
* [Druid](https://druid.apache.org)
- * [Spark](https://spark.apache.org)
-* <b>Maven deployable</b> and registered with the [Central
Repository](https://search.maven.org/#search|ga|1|DataSketches).
+ * [Spark](https://github.com/apache/datasketches-spark)
+ * [PostgreSQL](https://github.com/apache/datasketches-postgresql)
+ * [Hadoop/Hive](https://github.com/apache/datasketches-hive)
+ * [Pig](https://github.com/apache/datasketches-pig)
+
+* The Java-based sketches are registered with the <b>Maven Central
Repository</b>. For example:
[DataSketches-Java](https://search.maven.org/search?q=datasketches-java).
* Extensive documentation with the systems developer in mind.
* Designed for production environments:
- * Available in multiple languages: Java, C++,
[Python](https://github.com/apache/datasketches-python)
- * Binary compatible across systems and languages
+ * Available in multiple languages:
[Java](https://github.com/apache/datasketches-java),
[C++](https://github.com/apache/datasketches-cpp),
[Python](https://github.com/apache/datasketches-python), and
[Go](https://github.com/apache/datasketches-go).
+ * Binary compatible across systems and languages. For example, a sketch
can be built and loaded in a C++ platform, then serialized and transported to a
Java platform where it can be merged with other sketches and queried.
### Built-In, General Purpose Functions
* General purpose [Memory
Component]({{site.docs_dir}}/Memory/MemoryComponent.html) for managing data off
the Java Heap.
This enables systems designers the ability to manage their own large data
heaps with
dedicated processor threads that would otherwise put undue pressure on the
Java heap and
-its garbage collection.
+its garbage collection. Starting with Java Version 9.0.0, this functionality
is now native to the Java 25 language.
* General purpose implementaion of Austin Appleby's 128-bit MurmurHash3
algorithm,
with a number of useful extensions.
@@ -58,8 +60,7 @@ its garbage collection.
* Reproducible Characterization Studies
* All our published speed and accuracy performance results can be
reproduced using the code included in the
[Characterization](https://github.com/apache/datasketches-characterization)
repository.
-* Comprehensive Javadocs that satisfy
-[JDK8
Javadoc](https://docs.oracle.com/javase/8/docs/technotes/guides/javadoc/index.html)
standards.
+* Comprehensive Javadocs.
### Opportunities to Extend
@@ -86,15 +87,23 @@ its garbage collection.
### Quantiles
-* [Quantiles Sketch
Overview]({{site.docs_dir}}/Quantiles/QuantilesSketchOverview.html). Get normal
or inverse PDFs or CDFs of the distributions of any numeric value from your raw
data in a single pass with well defined error bounds on the results.
-
-### Frequent Items
+#### [Four families of Quantile
algorithms]({{site.docs_dir}}/QuantilesAll/QuantilesOverview.html)
+Get normal or inverse PDFs or CDFs of the distributions of any numeric value
from your raw data in a single pass with well defined error bounds on the
results.
+
+### Frequency
* [Frequent Items
Sketches]({{site.docs_dir}}/Frequency/FrequencySketchesOverview.html) Get the
most frequent items from a stream of items.
+* [CountMin sketch of Cormode and
Muthukrishnan](https://github.com/apache/datasketches-java/blob/main/src/main/java/org/apache/datasketches/count/CountMinSketch.java)
+* [Frequent Distinct
Tuples](https://github.com/apache/datasketches-java/blob/main/src/main/java/org/apache/datasketches/fdt/FdtSketch.java)
### Sampling
* [Reservoir Sampling]({{site.docs_dir}}/Sampling/ReservoirSampling.html)
Knuth's well known Reservoir sampling "Algorithm R", but extended to enable
merging across different sized reservoirs.
* [Weighted Sampling]({{site.docs_dir}}/Sampling/VarOptSampling.html) Edith
Cohen's famous sampling algorithm that enables computing subset sums of
weighted samples with optimum variance.
+* [Exact and Bounded Sampling Proportional to
Size](https://github.com/apache/datasketches-java/blob/main/src/main/java/org/apache/datasketches/sampling/EbppsItemsSketch.java)
+
+### Filters and Set Membership
+
+* [Bloom
Filter](https://github.com/apache/datasketches-java/blob/main/src/main/java/org/apache/datasketches/filters/bloomfilter/BloomFilter.java)
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