JavaOne – Make your CPU cores sweat with Parallel Streams

“Make your CPU cores sweat with Parallel Streams”

Speaker: Lukasz Pater

For more blog posts from JavaOne, see the table of contents


Started with the canonical Person/Car/age example to show what streams are [I think everyone at Javaone knows that]

Then showed code that finds all the prims under 10 milion that are palindromes when expressed in binary. Moores law is now relying on multi-core architecture. This example takes 1.6 seconds vs 8.6 seconds as parallel improvement. Five times faster.

Good analogy: If told to wash the fork, then the knife, then the… it is slow. If told to wash the dishes, you can optimize internally.

History of threads

  • JDK 1 – Threads – still good for small background task
  • JDK 5 – ExecutorService, concurrent objects
  • JDK 7 – fork/join framework – recursively decompose tasks into subtasks and then combine results
  • JDK 8 – parallel streams – use fork/join framework and Spliterator behind the scenes

Making a parallel stream

  • parallelStream() – for source
  • parallel() – anywhere in stream pipeline intermediate operation list

Fork Join Pool

  • Uses work stealing to balance tasks amongst workers in pool
  • All parallel streams use one common pool instance with # threads = # CPU cores – 1. That final thread is for the master to assign work.
  • Can change by setting system property java.util.concurrent.ForkJoinPool.common.parallelism. Must pass on commands line because first call to parallel stream resets it if set in code
  • If want custom fork join pool, create one and submit your stream to it. Does not recommend doing this. One reason you might want to is to add a timeout to the stream

Warnings

  • Avoid IO – burn CPU cycles waiting for IO/network
  • Use only for CPU intensive tasks
  • Be careful with nested paralle streams
  • Having many smaller tasks in the pool will better balance the workload
  • Don’t create your own fork join pool

Spliterator

  • splitable iterator
  • to traverse elements of a source in parallel
  • tryAdvance(Consumer) – do something if an element exists
  • trySplit() – partition off some elements to another spliterator leaving less elements in the original – fork so have tree of spliterators until run out of elements
  • characteristics()
  • estimateSize()
  • StreamSupport.stream(mySplierator, true) – creates parallel stream from spliterator – shouldn’t need to do this
  • ArrayList decomposes into equal sizes. LinkedList gives a smaller % of the elements because linear to get elements and want to minimize wait time
  • ArrayList and IntStream.range decompose well
  • LInkedLIst and Stream.iterate() decompose poorly – could even run out of memory
  • HashSet and TreeSet decompose in between

Other tips

  • Avoiding autoboxing also saves time. iterate() creates boxed objects where range() creates primitives
  • Parallel streams perform better where order doesn’t atter. findAny() or unordered().limit() [he missed the terminal operation in the limit example]
  • Avoid shared state
  • If have multiple calls to sequential() and parallel(), the last one wins and takes effect for the entire stream pipeline

My take:
Good discussion of performance and things to be beware of. My blog wasn’t live becase I couldn’t get internet in the room. I typed it live though! A couple typos like findFist() but nothing signficiant

JavaOne – Streams in JDK 8

“Streams in Java 8 – The good, the bad & the ugly”

Speaker: Simon Ritter & Stuart Marks
[Simon has the Twtter handle @speakjava; very cool]

For more blog posts from JavaOne, see the table of contents


Need to think differently. We are used to imperative programming with loops and variables.

Dealing wih exceptions
ugly code – three lines of code and hard to tell what it does

Problems:

  • looks like Perl
  • returns null (vs Optional or empty string)
  • split is called twice so wasted work
  • skipped URLDecoder.decode() because didn’t want to deal with a checked exception – but lost functionality. Problem caused by a missing API in Java so have to use decode.

Better approach:

  • use a method with a try/catch block; call that method from the stream
  • use Map.entry to simulate a tuple
  • Use single char (vs regex) in split. If only pass one character to split, far faster
  • split() is overloaded to take a numeric limit to how many are returned

Imperative streams
inside the for each is a print, and if statement and a LongAdder variable (good for frequent writes and infrequent reads)

then refactored to use mapToInt, a println and an if statement and a local variable. more complicated and still not functional

then switched to peek and no variabe but still an if statement (well a ternary)

finally switched to use a filter and count instead of sum

still not 100% functional because println is a side effect. ok for debugging

[good showing evolution to get functional]

Problems

  • Easy to misuse forEach() because feels familiar. But easily leads to side effects
  • Imperative thinking “for each of these I want to..”
  • Pause to consider if should use for each

Mixing internal and external iteration
for loop running 12 times and then getting data for each month with filter checking Month.of(x) – doesn’t work because x isn’t effectively final

“solve” effectively final by setting to different interim variable

IntStream.range(0,12).forEach – uses internal iteration but forEach. Marginaly better as don’t need interim variable

Instead return a nested map of Month to Map with nested grouping by so only need one iteration – the data stream

Problems

  • Going through data.stream() 12 times
  • forEach cheat
  • array not right data structure; it’s really a map of month to value

Hands on lab question
reduce (“”, (a,b) -> a+b) – works but inefficient because String concatenation

reduce(a,b) -> sb.append(b) – fails because ignores the first letter.

next attempt uses an if statement in reduce

then tried a custom collector. works but more complicated than necessary
Collector.of(StringBuilder::new, StringBuilder::append, StringBuilder::append, StringBuilder::toString

or just use Collectors.joining()

Problems

  • If not using a parameter, it is probably wrong
  • Side effects
  • if stateent version not associative so would fail when run in parallel

Misc

  • can’t use same stream multiple times
  • method references are slightly more efficient than lambdas because lambda gets added into a method in bytecode. Saves a level of indirection by using method reference. But only slightly
  • Calling .sorted() multiple times vs chaining comparing.thenComparing – the later is better [also works because preserves sort :)]
  • parallel streams do more work. might or might not complete faster. uses fork-join pool. number of threads defaults to number of CPUs. In Java9, this is # CPUs for container. On Jaa 8, it was for physical machine
  • Nested parallel streams is bad idea because using same threads so performance is worse. Can create ForkJoinPool if must. Buyer beware; this is an implementation specific behavior and tied to the profile of the machine you write it for.

My take: Fun start to he morning. I like that they covered common things in an entertaining way and not common things. Something to learn for everyone!

JavaOne – Maven BOF

“Maven 5 BOF”

Speaker: Brian Fox, Manfred Moser & Robert Scholte

For more blog posts from JavaOne, see the table of contents


[I was late because we talked more about JUnit 5 after the BOF]

Only 26.4% of Maven Central traffic is from Maven. Nothing else is more than 10% though; not even Ivy or Gradle

Some projects don’t have snapshots; instead every commit is a release

Talked about version ranges. Depends on proximity to your project rather than the latest version. Important to clean up pom dependencies before Java 9 so not in module path. Use Maven dependency plugin (analyze) to find unused ones. Make sure to use latest version of depedency plugin.

Maven won’t generate module descriptor. Different purpose. Not all modules are dependencies. More info in module descriptor. What to export is a decision that needs to be decided by developer. jdeps can generate a rough descriptor to get started based on binaries.

Can have .mvn file inside projects with preferences startig in Maven 3.3.5. For example, you can specify to provide more memory.

Shouldn’t be issues going from 3.3.5 to 3.5.9

Maven (dependency) resolver is now a standalone project