kanekv

# -*- ksh -*-
#
# If you use the GNU debugger gdb to debug the Python C runtime, you
# might find some of the following commands useful.  Copy this to your
# ~/.gdbinit file and it'll get loaded into gdb automatically when you
# start it up.  Then, at the gdb prompt you can do things like:
#
#    (gdb) pyo apyobjectptr
#    <module 'foobar' (built-in)>
#    refcounts: 1

adammw

/*
 * node-ffi-vlc v0.0.2
 * Object-orientated libVLC bindings for node.js implemented in javascript using node-ffi
 * Not for production use, use at your own risk, do with what you will.
 * See libvlc docs for more info, http://www.videolan.org/developers/vlc/doc/doxygen/html/group__libvlc.html
 */
var EventEmitter = require('events').EventEmitter,
    FFI = require("node-ffi");

var libVLC = new FFI.Library("libvlc", {

jfrost

-- Completely unused indexes:
SELECT relid::regclass as table, indexrelid::regclass as index
     , pg_size_pretty(pg_relation_size(indexrelid))
  FROM pg_stat_user_indexes
  JOIN pg_index
 USING (indexrelid)
 WHERE idx_scan = 0
   AND indisunique IS FALSE order by pg_relation_size(indexrelid);

muxx

<?php

include __DIR__ . '/pinba_configure.php';

pelletier

"""
This is a simple example of WebSocket + Tornado + Redis Pub/Sub usage.
Do not forget to replace YOURSERVER by the correct value.
Keep in mind that you need the *very latest* version of your web browser.
You also need to add Jacob Kristhammar's websocket implementation to Tornado:
Grab it here:
    http://gist.github.com/526746
Or clone my fork of Tornado with websocket included:
    http://github.com/pelletier/tornado
Oh and the Pub/Sub protocol is only available in Redis 2.0.0:

kolobaev

package seriesList

import (
	"fmt"
	"math"
	"strconv"

	"github.com/go-graphite/carbonapi/expr/helper"
	"github.com/go-graphite/carbonapi/expr/interfaces"
	"github.com/go-graphite/carbonapi/expr/types"

edeNFed

#!/usr/bin/python
# @lint-avoid-python-3-compatibility-imports
#
# profile  Profile CPU usage by sampling stack traces at a timed interval.
#          For Linux, uses BCC, BPF, perf_events. Embedded C.
#
# This is an efficient profiler, as stack traces are frequency counted in
# kernel context, rather than passing every stack to user space for frequency
# counting there. Only the unique stacks and counts are passed to user space
# at the end of the profile, greatly reducing the kernel<->user transfer.

narendrans

FROM centos:7

RUN yum install -y python3 python3-devel python3-pip unixODBC unixODBC-devel python3-setuptools gcc gcc-c++ https://download.dremio.com/odbc-driver/dremio-odbc-LATEST.x86_64.rpm && \
	pip3 install apache-superset sqlalchemy_dremio && \
	export LC_ALL=en_US.UTF-8 && \
	superset db upgrade && \
	superset init && \
	export FLASK_APP=superset && \
	flask fab create-admin --username admin --firstname admin --lastname admin --email admin@admin --password admin

danikin

// Tarantool quick test
// Copyright, Dennis Anikin 2016
//
// Quick disclaimer:
//
// This test shows 500K-1000K transactions per second on one CPU core
// and 600K-1600K queries per second on one CPU core.
//
// Based on the $6.57 per-month-price for the AWS t2.micro instance we can afford the tremendous number of 630bln queries for just $1
//

alexey-milovidov

Счётчики, метрики и трейспоинты в ClickHouse (черновик).

Мотивация

В ClickHouse разным образом реализовано некоторое количество функциональности, имеющей общие черты. Это:

• метрики на основе инкрементальных счётчиков (ProfileEvents);
• метрики на основе количества одновременных процессов (Metrics);
• метрики на основе асинхронно получаемых значений (AsynchronousMetrics);
• ограничения на сложность выполнения запроса (встроены в Settings);
• прогресс выполнения запроса (Progress, отправляется клиенту);