About Json to csv parser
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Key features of the Json to csv parser that are enabled through these drivers include:
- Convert JSON to CSV or CSV to JSON! - json-2-csv
- nsgirish/nifi-executescript-groovy-csv-json-parser - GitHub
- mrodrig/json-2-csv: Convert JSON to CSV or CSV to JSON!
- CSV and JSON Converter - Convert CSV to JSON and JSON to
- JSON Parser - Best JSON Formatter
- JSON Parser - Online JSON Formatter
- JSON Parser - The Best Json Beautifier
This is the tenth part of my syslog-ng tutorial. Last time, we learned about syslog-ng filters. Today, we learn about message parsing using syslog-ng.You can watch the video or read the text below.Parsing createsname-value pairs from log messages using parsers. It is probably the most interesting but also the most complex part of syslog-ng.By default, syslog-ng tries to parse all incoming log messages as if they were formatted according to the RFC 3164 or old/BSD syslog specification. This creates a number of macros, including MESSAGE, which contains the actual log message. You can then use other parsers to further parse the content of the MESSAGE macro. It does not stop here: you can parse the content of the resulting macros as well. This way, you can create complex parser chains that extract useful information from log messages.When we learned about sources, I mentioned the no-parse flag. This way, RFC 3164 parsing is disabled, and you can parse the whole message. This is useful for a JSON or CSV formatted log message.Why is message parsing important? There are two main use cases. Having log messages available as name-value pairs allows a lot more precise filtering. For example, you can create alerts within syslog-ng for a specific username in login messages. It is also possible to save/forward only relevant data from a longer log message, saving significant amount of storage and/or network traffic.PatternDB parserThe PatternDB message parser can extract information from unstructured messages into name-value pairs. Not just that, as it can also add status fields to log messages based on message text and do message classification, like LogCheck.Of course, syslog-ng does not know what is inside the log messages by itself. It needs an XML database describing log messages. There are some sample XML databases available online, but mostly you are on your own creating these databases for your logs. For example, in case of an SSH login failure can be described as:Parsed: app=sshd, user=root, source_ip=192.168.123.45Added: action=login, status=failureClassified as “violation”JSON parserThe JSON parser turns JSON-based log messages into name-value pairs. Yes, JSON is a structured log format. However, all incoming log messages are treated by syslog-ng as plain text. You have to instruct syslog-ng to use a parser and turn the message into name-value pairs.CSV parserThe CSV parser can parse columnar data into name-value pairs. A typical example is the Apache access log file, even if the fields are not separated by commas. In this example, you can see that each column has a name. Later, one of the resulting name-value pairs, the name of the authenticated user, is used in a file name.parser p_apache { csv-parser(columns("APACHE.CLIENT_IP", "APACHE.IDENT_NAME", "APACHE.USER_NAME", "APACHE.TIMESTAMP", "APACHE.REQUEST_URL", "APACHE.REQUEST_STATUS", "APACHE.CONTENT_LENGTH", "APACHE.REFERER", "APACHE.USER_AGENT", "APACHE.PROCESS_TIME", "APACHE.SERVER_NAME") flags(escape-double-char,strip-whitespace) delimiters(" ") quote-pairs('""[]') );};destination d_file { file("/var/log/messages-${APACHE.USER_NAME:-nouser}"); };log { source(s_local); parser(p_apache); destination(d_file);};Key=value parserThe key=value parser can find key=value pairs in log messages. It was introduced in syslog-ng 3.7. This format is typical for firewall logs, but also used by many other applications. Here are some example log messages:Aug 4 13:22:40 centos kernel: IPTables-Dropped:
