trait FieldExtractor[T] extends AnyRef
A FieldExtractor may be used to extract data from a Record. It
may be used directly via the extractFrom method, or more commonly
may be used as an operand to a Record, like
rec(fieldExtractor)
.
Extractors are meant to be more than a simple index into a record. Rather, they can retrieve any data based on a record, based on that record's template and values. Common uses of extractors are to extract data from a particular field regardless of the actual template being used, or to generate a computed value based on fields in a record, such as returning a string value for a field that is encoded as an integer.
The type parameter T
is a convenience feature. Implementations of
FieldExtractor normally have to use rec(i)
under the hood, which returns Any
. As such, a cast will
be made at some point, and a ClassCastException
may be thrown if
care is not taken. It is suggested that implementers of objects that
implement FieldExtractor
should include a constructor that takes
the class type as an argument, and do type checking based on the
record field type in order to throw an error during extractor
construction rather than during use.
- T
the type the extractor should return
- See also
Record
- Alphabetic
- By Inheritance
- FieldExtractor
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
Abstract Value Members
- abstract def extractFrom(rec: Record): Option[T]
Returns the value of the field referenced by the extractor from from the record as an Option.
Returns the value of the field referenced by the extractor from from the record as an Option. The value may be
None
if this extractor does not reference a field in this record.- rec
The record from which to extract the value.
- returns
The value referenced from the record or
None
.
Concrete Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable])
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
This is documentation for Mothra, a collection of Scala and Spark library functions for working with Internet-related data. Some modules contain APIs of general use to Scala programmers. Some modules make those tools more useful on Spark data-processing systems.
Please see the documentation for the individual packages for more details on their use.
Scala Packages
These packages are useful in Scala code without involving Spark:
org.cert.netsa.data
This package, which is collected as the
netsa-data
library, provides types for working with various kinds of information:org.cert.netsa.data.net
- types for working with network dataorg.cert.netsa.data.time
- types for working with time dataorg.cert.netsa.data.unsigned
- types for working with unsigned integral valuesorg.cert.netsa.io.ipfix
The
netsa-io-ipfix
library provides tools for reading and writing IETF IPFIX data from various connections and files.org.cert.netsa.io.silk
To read and write CERT NetSA SiLK file formats and configuration files, use the
netsa-io-silk
library.org.cert.netsa.util
The "junk drawer" of
netsa-util
so far provides only two features: First, a method for equipping Scala scala.collection.Iterators with exception handling. And second, a way to query the versions of NetSA libraries present in a JVM at runtime.Spark Packages
These packages require the use of Apache Spark:
org.cert.netsa.mothra.datasources
Spark datasources for CERT file types. This package contains utility features which add methods to Apache Spark DataFrameReader objects, allowing IPFIX and SiLK flows to be opened using simple
spark.read...
calls.The
mothra-datasources
library contains both IPFIX and SiLK functionality, whilemothra-datasources-ipfix
andmothra-datasources-silk
contain only what's needed for the named datasource.org.cert.netsa.mothra.analysis
A grab-bag of analysis helper functions and example analyses.
org.cert.netsa.mothra.functions
This single Scala object provides Spark SQL functions for working with network data. It is the entirety of the
mothra-functions
library.