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Um Case de Arquitetura Distribuída
para Indexação, Armazenamento e
 Análise de Logs em Tempo Real

         Juan Lopes
COMPLEX EVENT
   PROCESSING
TIME SERIES
REAL-TIME
LOGS
CENTENAS DE
SERVIDORES
marvin@goldenheart ~ $ ssh root@deepthought
****
WELCOME TO 1 OF YOUR 38,157,987 SERVERS.
TRY THE VEAL. IT'S THE BEST IN THIS FARM.
****

root@deepthought ~ $ tail -f /var/log.txt




                       COMO ACESSAR
                           OS LOGS?
COMO
"DEBUGAR"?
CENTRALIZAR
  INDEXAR
3TB / DIA
3TB / DIA
10.000.000.000 MSGS / DIA
36 MB / SEGUNDO
TWITTER
400.000.000 MSGS / DIA
EM JUNHO/2012
LOGGLY
Amplamente utilizado
Primeira opção para cloud
Maior plano não-custom: 12GB/dia
Preço: $1,779/mês
GRAYLOG2
Open Source
Self-hosted
Arquitetura de partes móveis
MongoDB
ElasticSearch
AMQP
SPLUNK
Famoso na área de BigData
Destinado ao mundo Enterprise
Muitos gráficos e relatórios
$6,000 one-time fee: 500MB/dia
500MB < 3TB :(
JAVA
HOTSPOT
java.util.concurrent
VISÃO GERAL


                            Armazenar


  mensagens   Interpretar


                             Indexar
RFC 3164: SYSLOG

 <34>Oct 11 22:14:15 mymachine su: 'su
 root' failed for lonvick on /dev/pts/8

 <priority = facility*8+severity>
 <date/time>
 <host>
 <process>
 <message>
CHAVE: VALOR

message    <34>Oct 11 22:14:15 mymachine su: 'su root'
           failed for lonvick on /dev/pts/8
text       su, root, failed, for, lonvick, on, /dev/pts/8

facility   AUTH
severity   CRITICAL
date       20121011
time       221415
host       mymachine
process    su
?
MG4J
 Egothor
    Nutch
    Oxyus
  BDDBot
Zilverline
     YaCy
Compass
      Lius
   Regain
 Piscator
 Hounder
 HSearch
<FIELD:CONTENT, DOC*>

TEXT:ABACAXI ➜ 1, 3, 9
TEXT:BANANA ➜ 2, 3, 10, 42
TEXT:CAJU ➜ 3, 11, 50
BAIXA ENTROPIA
<10% de termos únicos
menor overhead por mensagem


        MESSAGE BAG
VISÃO GERAL


                            Armazenar




 Interpretar   Bufferizar




                             Indexar
<DOC, FREQ, POSITION*>

1, 4 ➜ 5, 6, 10, 20
3, 1 ➜ 40
9, 4 ➜ 6, 7, 8, 9
SCORES NÃO
  IMPORTAM
NORMAL
INDEXAÇÃO      BUSCA
       Field   QueryParser
   Document    Query
 IndexWriter   IndexSearcher
HARDCORE
 INDEXAÇÃO       BUSCA
TokenStream      TermPositions
     Document    FieldCache
   IndexWriter   IndexReader
CULPA DA WIDESCREEN




CULPA DA WIDESCREEN
WEB INTERFACE
Jersey (REST API)
Backbone.js
CometD
WEB INTERFACE
Jersey (REST API)
Backbone.js
CometD           "app:apache     http 404"?




               engine                    browser




              "OK. listen:
              /comet/1234568790abcdef"
CULPA DA WIDESCREEN




CULPA DA WIDESCREEN
COMMAND-LINE INTERFACE
Cara e coragem
HttpClient
CometD




       /intelie/lognit-cli
REALTIME (AKA TAIL -F)

          EVENTS




                   subscriber
LIGHTWEIGHT TERM TRIE
ABRAÇO
ABRIGO
CHOCOLATE
                          <RAIZ>




                  ABR              CHOCOLATE



            AÇO         IGO
AGREGAÇÃO (AKA WC -L)

         EVENTS
~10.000 eventos / segundo




http
1 evento / segundo




http => count()
~100 eventos / segundo




http => count()
    by host
~100 eventos / 30 segundos




 http => count()
     by host
every 30 seconds
~100 eventos / 30 segundos




http => avg(cputime#)
        by host
   every 30 seconds
CULPA DA WIDESCREEN




CULPA DA WIDESCREEN
É PRECISO
ESCALAR
taxa de leitura
      MODERADA
 taxa de escrita
   ALTÍSSIMA
dependência entre os dados
         BAIXA
SHARDING


                         engine




                Load
UDP/TCP 514              engine
              Balancer




                         engine
Cluster

engine




engine   engine
Cluster

engine




                   engine
engine
Cluster

engine

                    Web     HTTP
                   Server
engine   engine                    usuário




                   Broker
Cluster

engine

                    Web     HTTP
                   Server
engine   engine                    usuário
Cluster

engine

         Multicast   engine   HTTP



engine                               usuário
MULTICAST
JChannel channel = new JChannel();
channel.setReceiver(new ReceiverAdapter() {
    public void receive(Message msg) {
        System.out.println(
            msg.getSrc() + ": " + msg.getObject());
    }
});

channel.connect("meuCanalDeChat");

BufferedReader reader = new BufferedReader(
                        new InputStreamReader(System.in));
while(true) {
    String line = reader.readLine();
    channel.send(null, line);
}
STACK CONFIGURÁVEL
TUDO ESTÁ DISTRIBUÍDO
BUSCA


 engine
           10

                   mergesort, take 10

          10    last 10 "http_status:   10
 engine
                        404"
                                             usuário
          10


 engine
BUSCA


 engine
           10
                    mergesort, take 10


          10    last 10 "http_status:    10
 engine                  404"
                before {id:84324814}
                                              usuário
          10


 engine
AGREGAÇÃO

        http 200 => count() by host

 host                count
 foo                 1234
 bar                 2345
 baz                 3456
AGREGAÇÃO


   count() + count() + count()




  engine      engine       engine
AGREGAÇÃO

        http 200 => avg(time) by host

 host                 avg_time
 foo                  0.888889
 bar                  0.224568
 baz                  5.623424
AGREGAÇÃO


   avg(time) + avg(time) + avg(time)
                   ?




  engine         engine         engine
AGREGAÇÃO


    sum(time) + sum(time) + sum(time)
 count(time) + count(time) + count(time)




  engine          engine         engine
AGREGAÇÃO


    sum(time) + sum(time) + sum(time)
 count(time) + count(time) + count(time)




  engine          engine         engine
E EM PRODUÇÃO?
3.5BI DE MENSAGENS
1TB DE DADOS ORIGINAIS
    180GB DE ÍNDICE
3 SERVIDORES (LOAD < 0.2)
UMA ÚLTIMA COISA
1700+
          TESTS

99%
LINES
COVERED
OBRIGADO!

     /juanplopes

     @juanplopes

     intelie.com.br

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