randomstatistic

import io.gatling.commons.stats.{KO, OK}
import io.gatling.commons.util.TimeHelper._
import io.gatling.core.Predef._
import io.gatling.core.action.{Action, ExitableAction}
import io.gatling.core.action.builder.ActionBuilder
import io.gatling.core.stats.StatsEngine
import io.gatling.core.stats.message.ResponseTimings
import io.gatling.core.structure.ScenarioContext
import io.gatling.core.util.NameGen

randomstatistic

Java:
  http://java-performance.com/
  
Linux:
  perf (https://perf.wiki.kernel.org/index.php/Main_Page)
  
  perf can be a bit finicky to set up though, One of the most interesting payoffs for the effort is getting cool flame graphs of cpu usage, like this example:
http://www.brendangregg.com/FlameGraphs/cpu-mixedmode-flamegraph-java.svg (from the blog post http://techblog.netflix.com/2015/07/java-in-flames.html)
 
Install perf:

randomstatistic

import java.util.Map.Entry

import com.typesafe.config.{ Config, ConfigRenderOptions, ConfigValue, ConfigValueFactory }
import org.mindrot.jbcrypt.BCrypt

import scala.io.{ Codec, Source }
import scala.collection.JavaConverters._
import scala.util.Try
import scala.util.matching.Regex

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import io.lettuce.core.RedisURI
import io.lettuce.core.cluster.{ ClusterClientOptions, ClusterTopologyRefreshOptions, RedisClusterClient }

import scala.util.Random

object MGet {
  def main(args: Array[String]): Unit = {
    val host = args(0)
    val port = args(1).toInt

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import java.io.Closable
import scala.util.control.NonFatal
import scala.util.{ Success, Try }

// This should really be scala-standard-lib.
object TryWithResources {
  def withClose[T <: Closeable, V](closable: T)(f: T => V): V = {
    (Try(f(closable)), Try(closable.close())) match {
      case (Success(v), Success(_)) => v
      case (a, b) => throw preferFirstException(a, b).get

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#!/bin/bash

dir=$1
if [ "$1" == "" ]; then
    echo "Must provide a directory as an argument"
    exit 1
fi

ftypes=$(find $1 -type f -size +10c | grep -E ".*\.[a-zA-Z0-9]*$" | sed -e 's/.*\(\.[a-zA-Z0-9]*\)$/\1/' | sort | uniq)

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import org.apache.zookeeper.server.{NIOServerCnxn, ZooKeeperServer}
import java.net.{ServerSocket, InetSocketAddress}
import kafka.server.{KafkaServer, KafkaConfig}
import kafka.producer.{ProducerConfig, Producer}
import java.util.Properties
import kafka.serializer.{DefaultEncoder, StringEncoder}
import java.io.File
import scala.util.Random
import kafka.admin.AdminUtils

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import java.io.FileNotFoundException
import java.util.zip.GZIPInputStream

import scala.io.Codec

object ClasspathReader {
  def getResourceAsStream(filename: String) = {
    // why doesn't the more scala-like getClass.getResourceAsStream work?
    val inputStream = Thread.currentThread().getContextClassLoader().getResourceAsStream(filename)
    if (inputStream == null) throw new FileNotFoundException(s"Couldn't find $filename on the classpath")

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import java.util.concurrent.locks.ReentrantLock

import scala.concurrent.{ExecutionContext, Future, Promise}
import scala.concurrent.duration._

class LeakyBucket(dripEvery: FiniteDuration, maxSize: Int) {
  require(maxSize > 0, "A bucket must have a size > 0")
  private val dripEveryNanos = dripEvery.toNanos

  private val lock = new ReentrantLock()

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The idea is to add calculated fields to the “fl” of your query that match the components of your query. 
Solr 4.0+ allows calculated functions in your field list using a <field name>:<function> syntax, and one of the available functions is “query”.

This seems like a vaguely unpleasant way to determine which clauses matched, but I could see it working. I think it would go something like:

q=colA:foo OR colB:bar&fl=*,score,matchedColA:query({!standard q=“colA:foo”},0),matchedColB:query({!standard q=“colB:bar”},0)

Presumably the field matchedColA would be non-zero if colA:foo matched on that document, and matchedColB would be non-zero 
if colB:bar matched.
(I’m actually not sure if “standard” works as the name of the default query parser, but whatever, the idea is that it needs to match the relevant bit of your query.)