Date: Fri, 13 May 2022 11:44:22 GMT From: Po-Chuan Hsieh <sunpoet@FreeBSD.org> To: ports-committers@FreeBSD.org, dev-commits-ports-all@FreeBSD.org, dev-commits-ports-main@FreeBSD.org Subject: git: 8172bd00a7ef - main - devel/py-ddsketch: Add py-ddsketch 2.0.2 Message-ID: <202205131144.24DBiMWf062328@gitrepo.freebsd.org>
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The branch main has been updated by sunpoet: URL: https://cgit.FreeBSD.org/ports/commit/?id=8172bd00a7efe63c77eea0afcecb0232fa0d7a3a commit 8172bd00a7efe63c77eea0afcecb0232fa0d7a3a Author: Po-Chuan Hsieh <sunpoet@FreeBSD.org> AuthorDate: 2022-05-13 11:27:19 +0000 Commit: Po-Chuan Hsieh <sunpoet@FreeBSD.org> CommitDate: 2022-05-13 11:39:10 +0000 devel/py-ddsketch: Add py-ddsketch 2.0.2 This is the Python implementation of the distributed quantile sketch algorithm DDSketch. DDSketch has relative-error guarantees for any quantile q in [0, 1]. That is if the true value of the qth-quantile is x then DDSketch returns a value y such that |x-y| / x < e where e is the relative error parameter. (The default here is set to 0.01.) DDSketch is also fully mergeable, meaning that multiple sketches from distributed systems can be combined in a central node. Our default implementation, DDSketch, is guaranteed to not grow too large in size for any data that can be described by a distribution whose tails are sub-exponential. We also provide implementations (LogCollapsingLowestDenseDDSketch and LogCollapsingHighestDenseDDSketch) where the q-quantile will be accurate up to the specified relative error for q that is not too small (or large). Concretely, the q-quantile will be accurate up to the specified relative error as long as it belongs to one of the m bins kept by the sketch. If the data is time in seconds, the default of m = 2048 covers 80 microseconds to 1 year. WWW: https://github.com/DataDog/sketches-py --- devel/Makefile | 1 + devel/py-ddsketch/Makefile | 23 +++++++++++++++++++++++ devel/py-ddsketch/distinfo | 3 +++ devel/py-ddsketch/pkg-descr | 19 +++++++++++++++++++ 4 files changed, 46 insertions(+) diff --git a/devel/Makefile b/devel/Makefile index 0ef5f85f32a3..42eb39e75526 100644 --- a/devel/Makefile +++ b/devel/Makefile @@ -4455,6 +4455,7 @@ SUBDIR += py-dateutils SUBDIR += py-datrie SUBDIR += py-dbus + SUBDIR += py-ddsketch SUBDIR += py-ddt SUBDIR += py-ddtrace SUBDIR += py-debtcollector diff --git a/devel/py-ddsketch/Makefile b/devel/py-ddsketch/Makefile new file mode 100644 index 000000000000..a8eb7d9e70e2 --- /dev/null +++ b/devel/py-ddsketch/Makefile @@ -0,0 +1,23 @@ +# Created by: Po-Chuan Hsieh <sunpoet@FreeBSD.org> + +PORTNAME= ddsketch +PORTVERSION= 2.0.2 +CATEGORIES= devel python +MASTER_SITES= CHEESESHOP +PKGNAMEPREFIX= ${PYTHON_PKGNAMEPREFIX} + +MAINTAINER= sunpoet@FreeBSD.org +COMMENT= Distributed quantile sketches + +LICENSE= APACHE20 + +BUILD_DEPENDS= ${PYTHON_PKGNAMEPREFIX}setuptools_scm>=0:devel/py-setuptools_scm@${PY_FLAVOR} +RUN_DEPENDS= ${PYTHON_PKGNAMEPREFIX}protobuf>=3.0.0,1:devel/py-protobuf@${PY_FLAVOR} \ + ${PYTHON_PKGNAMEPREFIX}six>=0:devel/py-six@${PY_FLAVOR} + +USES= python:3.7+ +USE_PYTHON= autoplist concurrent distutils + +NO_ARCH= yes + +.include <bsd.port.mk> diff --git a/devel/py-ddsketch/distinfo b/devel/py-ddsketch/distinfo new file mode 100644 index 000000000000..1c0f6bd69899 --- /dev/null +++ b/devel/py-ddsketch/distinfo @@ -0,0 +1,3 @@ +TIMESTAMP = 1652122529 +SHA256 (ddsketch-2.0.2.tar.gz) = 00c7f9d376c2abe8f9290d10cb3c712cd9effcdcd4477147553813ce54c97fee +SIZE (ddsketch-2.0.2.tar.gz) = 28932 diff --git a/devel/py-ddsketch/pkg-descr b/devel/py-ddsketch/pkg-descr new file mode 100644 index 000000000000..a3621b68d57c --- /dev/null +++ b/devel/py-ddsketch/pkg-descr @@ -0,0 +1,19 @@ +This is the Python implementation of the distributed quantile sketch algorithm +DDSketch. DDSketch has relative-error guarantees for any quantile q in [0, 1]. +That is if the true value of the qth-quantile is x then DDSketch returns a value +y such that |x-y| / x < e where e is the relative error parameter. (The default +here is set to 0.01.) DDSketch is also fully mergeable, meaning that multiple +sketches from distributed systems can be combined in a central node. + +Our default implementation, DDSketch, is guaranteed to not grow too large in +size for any data that can be described by a distribution whose tails are +sub-exponential. + +We also provide implementations (LogCollapsingLowestDenseDDSketch and +LogCollapsingHighestDenseDDSketch) where the q-quantile will be accurate up to +the specified relative error for q that is not too small (or large). Concretely, +the q-quantile will be accurate up to the specified relative error as long as it +belongs to one of the m bins kept by the sketch. If the data is time in seconds, +the default of m = 2048 covers 80 microseconds to 1 year. + +WWW: https://github.com/DataDog/sketches-py
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