cpet/openbsd-ports
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
openbsd-ports/www/logswan/Makefile

36 lines
738 B
Makefile
Raw Normal View History

Update logswan to 2.1.3.
2020-01-17 20:22:03 +00:00
# $OpenBSD: Makefile,v 1.21 2020/01/17 20:22:03 fcambus Exp $
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
- update to logswan-1.04 from maintainer Frederic Cambus
2016-01-11 08:31:27 +00:00
COMMENT = fast web log analyzer using probabilistic data structures
move GH_* to the top of Makefile; ok maintainer
2016-01-11 13:56:28 +00:00
Update logswan to 2.1.3.
2020-01-17 20:22:03 +00:00
V = 2.1.3
Update to www/logswan-1.05 from Frederic Cambus (MAINTAINER) OK sthen@
2016-03-11 20:03:06 +00:00
DISTNAME = logswan-$V
Consistency in email address. ok maintainer
2016-01-11 14:11:08 +00:00
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
CATEGORIES = www
Update logswan to 1.07.
2017-02-14 13:55:13 +00:00
HOMEPAGE = https://www.logswan.org/
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
Update my mail address
2016-09-22 12:57:17 +00:00
MAINTAINER = Frederic Cambus <fcambus@openbsd.org>
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
# BSD
replace simple PERMIT_PACKAGE_CDROM=Yes with PERMIT_PACKAGE=Yes
2019-07-12 20:50:46 +00:00
PERMIT_PACKAGE = Yes
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
Update to www/logswan-1.05 from Frederic Cambus (MAINTAINER) OK sthen@
2016-03-11 20:03:06 +00:00
# uses pledge()
Update logswan to 2.0.0.
2018-03-16 14:33:59 +00:00
WANTLIB += c jansson m maxminddb
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
Update to www/logswan-1.05 from Frederic Cambus (MAINTAINER) OK sthen@
2016-03-11 20:03:06 +00:00
MASTER_SITES = https://github.com/fcambus/logswan/releases/download/$V/
Update logswan to 2.0.2 and add COMPILER directive so it keeps building on GCC arches after the latest net/libmaxminddb port changes.
2018-08-05 20:41:15 +00:00
COMPILER = base-clang ports-gcc
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
MODULES = devel/cmake
LIB_DEPENDS = devel/jansson \
Update logswan to 2.0.0.
2018-03-16 14:33:59 +00:00
net/libmaxminddb
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
Update logswan to 2.0.0.
2018-03-16 14:33:59 +00:00
CONFIGURE_ARGS = -DGEOIP2DIR=${LOCALSTATEDIR}/db/GeoIP
import ports/www/logswan, from Frederic Cambus, tweak from me, ok benoit@, earlier version ok jung@ Logswan is a fast Web log analyzer using probabilistic data structures. It is targeted at very large log files, typically APIs logs. It has constant memory usage regardless of the log file size, and takes approximatively 4MB of RAM. Unique visitors counting is performed using two HyperLogLog counters (one for IPv4, and another one for IPv6), providing a relative accuracy of 0.10%.
2015-11-05 16:19:04 +00:00
post-install:
${INSTALL_DATA_DIR} ${PREFIX}/share/doc/logswan
${INSTALL_DATA} ${WRKSRC}/README.md ${PREFIX}/share/doc/logswan
.include <bsd.port.mk>
Reference in New Issue Copy Permalink