squito

CDP Port Jira Backport Skill

Cursor agent skill for porting and backporting CDPD fixes to CDP release branches.

Files

File	Purpose
SKILL.md	Main skill — workflow, guardrails, phases 1–7
branch-mapping.md	CDH branch ↔ version mapping rules

squito

import scala.util.matching.Regex
import collection.mutable. { HashMap, MultiMap, Set, HashSet}

/**
 * Helper function, just to see if I got the regex correct
 */
def checkMatch(p: String, t: String): Option[Seq[String]] = {
  p.r.findFirstMatchIn(t). map { m =>
    (1 to m.groupCount).map { m.group(_) }
  }

squito

#!/usr/bin/env python

## Makes it easy to run tests in a loop
## Just a small bit of automation around something like
##      ls quanta_cache.py test/test_quanta_cache.py | entr -r python -m pytest test/test_quanta_cache.py
## but that is just complex enough I would never remember

## If you want to test `jira.py` in a loop, run:
##
##     test/test_loop.py --test jira.py

squito

import java.security.PrivilegedExceptionAction
import org.apache.hadoop.security.UserGroupInformation
import org.apache.hadoop.fs.Path
import org.apache.hadoop.fs.FileSystem
import org.apache.hadoop.conf.Configuration

object AccessControlCheck {
  
  val privilegedPath = "/some/path/with/limited/access"

squito

import java.util.ArrayList;

public class Test implements Runnable {

  public static class OOMer implements Runnable {
    public void run() {
      System.out.println("Starting oomer");
      ArrayList<byte[]> stuff = new ArrayList<>();
      while (true) {
        stuff.add(new byte[100000000]);

squito

// run with "--conf spark.cleaner.referenceTracking=false"
// spin up our full set of executors
sc.parallelize(1 to 100, 100).map { x => Thread.sleep(1000); x}.collect()

def getLocalDirs(): Array[String] = {
  val clz = Class.forName("org.apache.spark.util.Utils")
  val conf = org.apache.spark.SparkEnv.get.conf
  val method = clz.getMethod("getConfiguredLocalDirs", conf.getClass())
  method.setAccessible(true)
  method.invoke(null, conf).asInstanceOf[Array[String]]

squito

// This is an example iterator that runs slowly, to demonstrate how SlowLoggingIterator works
// it just iterates over a range of ints, but puts in occassional delays, to simulate an iterator that is
// actually doing something more complex, eg. fetching records from a DB which is occassionaly slow.

class SlowIterator(start: Int, end: Int, delay: Long, every: Int) extends java.util.Iterator[Integer] {
  val underlying = (start until end).toIterator

  def hasNext(): Boolean = underlying.hasNext

  def next(): Integer = {

squito

creating a new thread pool thread 0 : tl = null
creating a new thread pool thread 1 : tl = null
creating a new thread pool thread 2 : tl = null
creating a new thread pool thread 3 : tl = null
creating a new thread pool thread 4 : tl = null
creating a new thread pool thread 5 : tl = null
creating a new thread pool thread 6 : tl = null
creating a new thread pool thread 7 : tl = null
creating a new thread pool thread 8 : tl = null
creating a new thread pool thread 9 : tl = null

squito

# filters out "apachespark" choice now
# notice what happens with
#  * bad input ("floop")
#  * real user that can't be assigned a jira ("fakeimran")
#  * selection from list ("imran")
#  * arbitrary user that can be assigned ("vanzin")


In [1]: from merge_spark_pr import *                                                                                                                                                                     

squito

// paste in
// https://gist.githubusercontent.com/squito/329d9cd82a21f645d592/raw/ca9217708293d6fe69ed6638f4feeb3038f8fd9c/reflector.scala

val xCat = spark.sessionState.catalog.externalCatalog

val catClient = get(xCat, "client")
catClient.reflectMethod("getConf", Seq("hive.metastore.uris", ""))
import org.apache.hadoop.fs.{FileSystem, Path}
val fs = FileSystem.get(sc.hadoopConfiguration)