brusic

rails_env = ENV['RAILS_ENV'] || ENV['RACK_ENV'] || 'development'

Split.redis = YAML.load_file(Rails.root.join('config/split.yml')).fetch(rails_env)

Split.configure do |config|
  adapter = Split::Persistence::RedisAdapter.with_config(
    lookup_by: :params_user_id,
    namespace: 'abtesting_participant_id',
    expire_seconds: 2_592_000, # 30 days
  )

brusic

curl -XPUT localhost:9200/test -d '{
  "settings": {
    "index": {
      "number_of_shards": 1,
      "number_of_replicas": 0
    }
  },
  "mappings": {
    "test" : {
        "properties" : {

brusic

sed -e 's/{"took":[0-9]*,"timed_out":false,"_shards":{"total":[0-9]*,"successful":[0-9]*,"failed":0},"hits":{"total":[0-9]*,"max_score":[0-9\.]*,"hits":\[\(.*\)\]}}$/\1/' -e 's/}},/}}\n/g' -e 's/{"_index"/{ "index":{"_index"/' -e 's/,"_score":[0-9\.]*, "_source" : /}}\n/g'

brusic

appender:
  socketA:
    type: org.apache.log4j.net.SocketAppender
    port: 9500
    remoteHost: logstash-server

  socketB:
    type: org.apache.log4j.net.SocketAppender
    port: 9501
    remoteHost: logstash-server

brusic

package org.elasticsearch.index.similarity;

import org.apache.lucene.search.similarities.DefaultSimilarity;
import org.elasticsearch.common.logging.ESLogger;
import org.elasticsearch.common.logging.Loggers;

public class NormRemovalSimilarity extends DefaultSimilarity {

	private ESLogger logger;

brusic

curl -XPOST localhost:9200/boosts -d '
{
  "settings": {
    "number_of_shards": 1,
    "number_of_replicas": 0
  },
  "mappings": {
    "doc": {
      "properties": {
        "text": {

brusic

{
  "query": {
    "match_all": {}
  },
  "filter": {
    "term": {
      "model": "vw"
    }
  },
  "facets": {

brusic

// TEST DATA

curl -XPUT http://localhost:9200/twitter/user/kimchy -d '{
    "name" : "Shay Banon"
}'

curl -XPUT http://localhost:9200/twitter/tweet/1 -d '{
    "user": "kimchy",
    "post_date": "2009-11-15T13:12:00",
    "message": "Trying out elasticsearch, so far so good?"

brusic

// define inside file timetest.m
function blank = timetest(x, y, MAX_ITR)
    m = length(y);
    x = [ones(m, 1) x];
    theta = zeros(size(x(1,:)))'; % initialize fitting parameters
    alpha = 0.07;
    
    for num_iterations = 1:MAX_ITR
        grad = (1/m).* x' * ((x * theta) - y);
        theta = theta - alpha .* grad;