tzachz

public class UserValidator {
    private Cryptographer cryptographer;
    
    public boolean checkPassword(String userName, String password) {
        User user = UserGateway.findByName(userName);
        if (user != User.NULL) {
            String codedPhrase = user.getPhraseEncodedByPassword();
            String phrase = cryptographer.decrypt(codedPhrase, password);
            if ("Valid Password".equals(phrase)) {
                Session.initialize();

tzachz

public class StaticClass {
    
    static {
        throwsException();
    }

    private static void throwsException() {
        throw new RuntimeException("bam!");
    }

tzachz

import org.json4s._
import org.json4s.jackson.JsonMethods.parse
import scala.io.Source.fromURL

object SparkAppStats {

  /**
   * (partial) representation of a Spark Stage object 
   */
  case class SparkStage(name: String, shuffleWriteBytes: Long, memoryBytesSpilled: Long, diskBytesSpilled: Long)

tzachz

package com.kenshoo.kripke.core

import com.yammer.metrics.Metrics
import com.yammer.metrics.core.{MetricName, Counter}
import org.apache.spark.Accumulator
import org.apache.spark.rdd.RDD

import scala.reflect.ClassTag

object CounterBackedAccumulatorUtil {

tzachz

import com.yammer.metrics.Metrics
import com.yammer.metrics.core.Gauge
import org.apache.spark.SparkContext

/**
 * Created by tzachz on 10/21/15
 */
object SparkContextInstrumentor {

  def instrument(context: SparkContext): SparkContext = {

tzachz

import java.text.SimpleDateFormat
import java.util.Date
import org.json4s._
import org.json4s.jackson.JsonMethods.parse
import scala.io.Source.fromURL

object SparkAppStats {

  val url = "http://<host>:4040/api/v1/applications/<app-name>/jobs"

tzachz

import java.io.{File, IOException}
import java.net.InetAddress

import org.apache.spark.SparkContext
import org.apache.spark.rdd.RDD
import org.slf4j.{Logger, LoggerFactory}

import scala.util.{Failure, Try}

object LocalDiskHealthCheck {

tzachz

import org.apache.spark.SparkContext
import org.apache.spark.sql.expressions.{MutableAggregationBuffer, UserDefinedAggregateFunction}
import org.apache.spark.sql.types._
import org.apache.spark.sql.{Column, Row, SQLContext}

/***
  * UDAF combining maps, overriding any duplicate key with "latest" value
  * @param keyType DataType of Map key
  * @param valueType DataType of Value key
  * @param merge function to merge values of identical keys

tzachz

// Inspired by https://gist.github.com/abesto/cdcdd38263eacf1cbb51
// Task creates a .dot file with all inter-module dependencies
// Supports any depth of nested modules

task moduleDependencyReport {
    doLast {
        def file = new File("project-dependencies.dot")
        file.delete()
        file << "digraph {\n"
        file << "splines=ortho\n"

tzachz

AnodotReporterConfiguration anodotConf = 
  new DefaultAnodotReporterConfiguration("your-token", 60, "https://api.anodot.com/api/v1/metrics");

Anodot3ReporterBuilder.builderFor(anodotConf)
  .build(metricRegistry)
  .start()