Blogs

Procesando logs con Nifi Grok y HIVE

Usando expresiones Grok para el mapeo y Hive para su explotación posterior

En esta ocasión vamos a hacer una prueba de cómo se pueden procesar de manera sencilla, para su posterior explotación con HIVE, los logs de un servidor apache usando

 Expresiones Grok
 Records de Nifi (Avro)
 Ficheros ORC

El punto de partida es un conjunto de ficheros con el access log de apache en tipo COMBINED. Lo que vamos a hacer es crear un flujo de NiFi con el que los vamos a transformar los logs en ficheros ORC. Una vez generados los dejaremos en una estructura de un filesystem remoto HDFS y los explotaremos con HIVE usando una external table. Para ello usaremos HDP 3.0 y HDF 3.2.0 de hortonworks

Un ejemplo de uno de los registros es el siguiente

185.234.217.54 - - [30/Sep/2018:06:25:05 +0200] "GET /user/register;jsessionid=57BC21D6C72B385C5EC87922BBAC26D2?ajax_form=1&element_parents=account%2Fmail%2F%23value&_wrapper_format=drupal_aja HTTP/1.1" 302 4107 "-" "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36"

Usando una expresión Grok y el processor ConvertRecord de Nifi convertimos el conjunto de eventos de un log de apache en un flowfile con los records en formato avro, para ello definiremos un GrokReader y AvroWriter.

 

 

Lo más destacado es que para definir el reader usaremos un fichero de patters y une expresiones Grok previamente definida en este fichero de patters (%{HTTPD_COMBINEDLOG}), que sirve para hacer match con el registro de apache especificado.

El fichero de patterns contiene el siguiente texto

 

USERNAME [a-zA-Z0-9._-]+
USER %{USERNAME}
EMAILLOCALPART [a-zA-Z][a-zA-Z0-9_.+-=:]+
EMAILADDRESS %{EMAILLOCALPART}@%{HOSTNAME}
INT (?:[+-]?(?:[0-9]+))
BASE10NUM (?<![0-9.+-])(?>[+-]?(?:(?:[0-9]+(?:\.[0-9]+)?)|(?:\.[0-9]+)))
NUMBER (?:%{BASE10NUM})
BASE16NUM (?<![0-9A-Fa-f])(?:[+-]?(?:0x)?(?:[0-9A-Fa-f]+))
BASE16FLOAT \b(?<![0-9A-Fa-f.])(?:[+-]?(?:0x)?(?:(?:[0-9A-Fa-f]+(?:\.[0-9A-Fa-f]*)?)|(?:\.[0-9A-Fa-f]+)))\b

POSINT \b(?:[1-9][0-9]*)\b
NONNEGINT \b(?:[0-9]+)\b
WORD \b\w+\b
NOTSPACE \S+
SPACE \s*
DATA .*?
GREEDYDATA .*
QUOTEDSTRING (?>(?<!\\)(?>"(?>\\.|[^\\"]+)+"|""|(?>'(?>\\.|[^\\']+)+')|''|(?>`(?>\\.|[^\\`]+)+`)|``))
UUID [A-Fa-f0-9]{8}-(?:[A-Fa-f0-9]{4}-){3}[A-Fa-f0-9]{12}
# URN, allowing use of RFC 2141 section 2.3 reserved characters
URN urn:[0-9A-Za-z][0-9A-Za-z-]{0,31}:(?:%[0-9a-fA-F]{2}|[0-9A-Za-z()+,.:=@;$_!*'/?#-])+

# Networking
MAC (?:%{CISCOMAC}|%{WINDOWSMAC}|%{COMMONMAC})
CISCOMAC (?:(?:[A-Fa-f0-9]{4}\.){2}[A-Fa-f0-9]{4})
WINDOWSMAC (?:(?:[A-Fa-f0-9]{2}-){5}[A-Fa-f0-9]{2})
COMMONMAC (?:(?:[A-Fa-f0-9]{2}:){5}[A-Fa-f0-9]{2})
IPV6 ((([0-9A-Fa-f]{1,4}:){7}([0-9A-Fa-f]{1,4}|:))|(([0-9A-Fa-f]{1,4}:){6}(:[0-9A-Fa-f]{1,4}|((25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)(\.(25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)){3})|:))|(([0-9A-Fa-f]{1,4}:){5}(((:[0-9A-Fa-f]{1,4}){1,2})|:((25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)(\.(25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)){3})|:))|(([0-9A-Fa-f]{1,4}:){4}(((:[0-9A-Fa-f]{1,4}){1,3})|((:[0-9A-Fa-f]{1,4})?:((25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)(\.(25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)){3}))|:))|(([0-9A-Fa-f]{1,4}:){3}(((:[0-9A-Fa-f]{1,4}){1,4})|((:[0-9A-Fa-f]{1,4}){0,2}:((25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)(\.(25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)){3}))|:))|(([0-9A-Fa-f]{1,4}:){2}(((:[0-9A-Fa-f]{1,4}){1,5})|((:[0-9A-Fa-f]{1,4}){0,3}:((25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)(\.(25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)){3}))|:))|(([0-9A-Fa-f]{1,4}:){1}(((:[0-9A-Fa-f]{1,4}){1,6})|((:[0-9A-Fa-f]{1,4}){0,4}:((25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)(\.(25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)){3}))|:))|(:(((:[0-9A-Fa-f]{1,4}){1,7})|((:[0-9A-Fa-f]{1,4}){0,5}:((25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)(\.(25[0-5]|2[0-4]\d|1\d\d|[1-9]?\d)){3}))|:)))(%.+)?
IPV4 (?<![0-9])(?:(?:[0-1]?[0-9]{1,2}|2[0-4][0-9]|25[0-5])[.](?:[0-1]?[0-9]{1,2}|2[0-4][0-9]|25[0-5])[.](?:[0-1]?[0-9]{1,2}|2[0-4][0-9]|25[0-5])[.](?:[0-1]?[0-9]{1,2}|2[0-4][0-9]|25[0-5]))(?![0-9])
IP (?:%{IPV6}|%{IPV4})
HOSTNAME \b(?:[0-9A-Za-z][0-9A-Za-z-]{0,62})(?:\.(?:[0-9A-Za-z][0-9A-Za-z-]{0,62}))*(\.?|\b)
IPORHOST (?:%{IP}|%{HOSTNAME})
HOSTPORT %{IPORHOST}:%{POSINT}

# paths
PATH (?:%{UNIXPATH}|%{WINPATH})
UNIXPATH (/([\w_%!$@:.,+~-]+|\\.)*)+
TTY (?:/dev/(pts|tty([pq])?)(\w+)?/?(?:[0-9]+))
WINPATH (?>[A-Za-z]+:|\\)(?:\\[^\\?*]*)+
URIPROTO [A-Za-z]([A-Za-z0-9+\-.]+)+
URIHOST %{IPORHOST}(?::%{POSINT:port})?
# uripath comes loosely from RFC1738, but mostly from what Firefox
# doesn't turn into %XX
URIPATH (?:/[A-Za-z0-9$.+!*'(){},~:;=@#%&_\-]*)+
#URIPARAM \?(?:[A-Za-z0-9]+(?:=(?:[^&]*))?(?:&(?:[A-Za-z0-9]+(?:=(?:[^&]*))?)?)*)?
URIPARAM \?[A-Za-z0-9$.+!*'|(){},~@#%&/=:;_?\-\[\]<>]*
URIPATHPARAM %{URIPATH}(?:%{URIPARAM})?
URI %{URIPROTO}://(?:%{USER}(?::[^@]*)?@)?(?:%{URIHOST})?(?:%{URIPATHPARAM})?

# Months: January, Feb, 3, 03, 12, December
MONTH \b(?:[Jj]an(?:uary|uar)?|[Ff]eb(?:ruary|ruar)?|[Mm](?:a|ä)?r(?:ch|z)?|[Aa]pr(?:il)?|[Mm]a(?:y|i)?|[Jj]un(?:e|i)?|[Jj]ul(?:y)?|[Aa]ug(?:ust)?|[Ss]ep(?:tember)?|[Oo](?:c|k)?t(?:ober)?|[Nn]ov(?:ember)?|[Dd]e(?:c|z)(?:ember)?)\b
MONTHNUM (?:0?[1-9]|1[0-2])
MONTHNUM2 (?:0[1-9]|1[0-2])
MONTHDAY (?:(?:0[1-9])|(?:[12][0-9])|(?:3[01])|[1-9])

# Days: Monday, Tue, Thu, etc...
DAY (?:Mon(?:day)?|Tue(?:sday)?|Wed(?:nesday)?|Thu(?:rsday)?|Fri(?:day)?|Sat(?:urday)?|Sun(?:day)?)

# Years?
YEAR (?>\d\d){1,2}
HOUR (?:2[0123]|[01]?[0-9])
MINUTE (?:[0-5][0-9])
# '60' is a leap second in most time standards and thus is valid.
SECOND (?:(?:[0-5]?[0-9]|60)(?:[:.,][0-9]+)?)
TIME (?!<[0-9])%{HOUR}:%{MINUTE}(?::%{SECOND})(?![0-9])
# datestamp is YYYY/MM/DD-HH:MM:SS.UUUU (or something like it)
DATE_US %{MONTHNUM}[/-]%{MONTHDAY}[/-]%{YEAR}
DATE_EU %{MONTHDAY}[./-]%{MONTHNUM}[./-]%{YEAR}
ISO8601_TIMEZONE (?:Z|[+-]%{HOUR}(?::?%{MINUTE}))
ISO8601_SECOND (?:%{SECOND}|60)
TIMESTAMP_ISO8601 %{YEAR}-%{MONTHNUM}-%{MONTHDAY}[T ]%{HOUR}:?%{MINUTE}(?::?%{SECOND})?%{ISO8601_TIMEZONE}?
DATE %{DATE_US}|%{DATE_EU}
DATESTAMP %{DATE}[- ]%{TIME}
TZ (?:[APMCE][SD]T|UTC)
DATESTAMP_RFC822 %{DAY} %{MONTH} %{MONTHDAY} %{YEAR} %{TIME} %{TZ}
DATESTAMP_RFC2822 %{DAY}, %{MONTHDAY} %{MONTH} %{YEAR} %{TIME} %{ISO8601_TIMEZONE}
DATESTAMP_OTHER %{DAY} %{MONTH} %{MONTHDAY} %{TIME} %{TZ} %{YEAR}
DATESTAMP_EVENTLOG %{YEAR}%{MONTHNUM2}%{MONTHDAY}%{HOUR}%{MINUTE}%{SECOND}

# Syslog Dates: Month Day HH:MM:SS
SYSLOGTIMESTAMP %{MONTH} +%{MONTHDAY} %{TIME}
PROG [\x21-\x5a\x5c\x5e-\x7e]+
SYSLOGPROG %{PROG:program}(?:\[%{POSINT:pid}\])?
SYSLOGHOST %{IPORHOST}
SYSLOGFACILITY <%{NONNEGINT:facility}.%{NONNEGINT:priority}>
HTTPDATE %{MONTHDAY}/%{MONTH}/%{YEAR}:%{TIME} %{INT}

# Shortcuts
QS %{QUOTEDSTRING}

# Log formats
SYSLOGBASE %{SYSLOGTIMESTAMP:timestamp} (?:%{SYSLOGFACILITY} )?%{SYSLOGHOST:logsource} %{SYSLOGPROG}:

# Log Levels
LOGLEVEL ([Aa]lert|ALERT|[Tt]race|TRACE|[Dd]ebug|DEBUG|[Nn]otice|NOTICE|[Ii]nfo|INFO|[Ww]arn?(?:ing)?|WARN?(?:ING)?|[Ee]rr?(?:or)?|ERR?(?:OR)?|[Cc]rit?(?:ical)?|CRIT?(?:ICAL)?|[Ff]atal|FATAL|[Ss]evere|SEVERE|EMERG(?:ENCY)?|[Ee]merg(?:ency)?)

HTTPDUSER %{EMAILADDRESS}|%{USER}
HTTPDERROR_DATE %{DAY} %{MONTH} %{MONTHDAY} %{TIME} %{YEAR}

# Log formats
HTTPD_COMMONLOG %{IPORHOST:clientip} %{HTTPDUSER:ident} %{HTTPDUSER:auth} \[%{HTTPDATE:timestamp}\] "(?:%{WORD:verb} %{NOTSPACE:request}(?: HTTP/%{NUMBER:httpversion})?|%{DATA:rawrequest})" %{NUMBER:response} (?:%{NUMBER:bytes}|-)
HTTPD_COMBINEDLOG %{HTTPD_COMMONLOG} %{QS:referrer} %{QS:agent}

# Error logs
HTTPD20_ERRORLOG \[%{HTTPDERROR_DATE:timestamp}\] \[%{LOGLEVEL:loglevel}\] (?:\[client %{IPORHOST:clientip}\] ){0,1}%{GREEDYDATA:message}
HTTPD24_ERRORLOG \[%{HTTPDERROR_DATE:timestamp}\] \[%{WORD:module}:%{LOGLEVEL:loglevel}\] \[pid %{POSINT:pid}(:tid %{NUMBER:tid})?\]( \(%{POSINT:proxy_errorcode}\)%{DATA:proxy_message}:)?( \[client %{IPORHOST:clientip}:%{POSINT:clientport}\])?( %{DATA:errorcode}:)? %{GREEDYDATA:message}
HTTPD_ERRORLOG %{HTTPD20_ERRORLOG}|%{HTTPD24_ERRORLOG}

# Deprecated
COMMONAPACHELOG %{HTTPD_COMMONLOG}
COMBINEDAPACHELOG %{HTTPD_COMBINEDLOG}

 

Una vez transformados los logs en flowfiles AVRO los transformaremos para convertir las fechas en unixtime. Usando para ello un processor tipo UpdateReord y la siguiente expresión

${field.value:toDate('dd/MMM/yyyy:HH:mm:ss', 'Europe/Madrid'):toNumber()}

Luego usaremos un processor tipo QueryRecord para eliminar los eventos que no contiene request, para ello usaremos la siguiente query

SELECT * from Flowfile where request is not null


Una vez filtrados convertiremos los records a nuevo esquema avro con un processor tipo CovertRecord (by path), usando el siguiente esquema, que almacenaremos en el servicio SchemaRegistry de HDF

{
 "type":"record",
 "name":"ApacheLogRecord",
 "namespace":"org.apache.nifi",
 "fields":[
    {"name":"CLIENT_IP","type":["null","string"]},
    {"name":"IDENT","type":["null","string"]},
    {"name":"AUTH","type":["null","string"]},
    {"name":"EVENT_DATE","type":["null","long"]},
    {"name":"VERB","type":["null","string"]},
    {"name":"REQUEST","type":["null","string"]},
    {"name":"HTTP_VERSION","type":["null","string"]},
    {"name":"RESPONSE","type":["null","int"]},
    {"name":"BYTES_SIZE","type":["null","int"]},
    {"name":"REFERRER","type":["null","string"]},
    {"name":"AGENT","type":["null","string"]}
 ]
}


Una vez tengamos los flowfiles con los records deseados, los transformaremos en ficheros ORC con el processor ConvertAvroToORC y los guardaremos en un directorio de HDFS (si queremos ordenado por yyyy/mm/dd para poder usar shard en HIVE) para poder explotarlos con HIVE

La tabla que crearemos sobre el directorio de HDFS será la siguiente

CREATE EXTERNAL TABLE APACHE_LOG (

   CLIENT_IP STRING,

   IDENT STRING,

   AUTH STRING,

   EVENT_DATE BIGINT,

   VERB STRING,

   REQUEST STRING,

   HTTP_VERSION STRING,

   RESPONSE INT, 

   BYTES_SIZE STRING,

   REFERRER STRING,

   AGENT STRING

) STORED AS ORC LOCATION '/user/nifi/poc/APACHE_LOG_POC'

 

Siguiendo este mismo esquema se podría

  • Generar Segmentos para Druid
  • Generar Segmentos en parquet
  • Hacer que un MiNiFi envíe los eventos a un nifi central y que éste los almacene
  • Hacer que un MiNifi envíe los eventos a un Kafka y que Nifi los lea de ahí

More Blog Entries

ZYLK Industry has been selected as one of the brightest “Big Data” startups in Europe

What is EDI? EDI is an incubation programme run by 20 partners across Europe. It gives the...

0 Comments