Devoxx 2016 - day 4: notes (2016/11/10)

Programming your body with chip implants

Pär Sikö

chip: 12mm / 2mm -- same as for pets

• rfid: entrance system
• nfc: smartcards: 1kb

issues

• battery -- energy harvesting
• communication technology
  • active

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Optional - The Mother of All Bikesheds

Stuart Marks

Optional

• java 8 (java.util)
• non-null ref (present) or empty (absent)
• primitives: OptionalInt, Long etc
• never use "null" as ref in Optional
• "limited mech for returntypes where null will very likely return errors" e.g. streams api: Optional prevents NPE's in chained calls
• issue NoSuchElementException

usage of Optional

• never call "Optional.get()" when you can prove that the Optional is present
• prefer alternatives to Optional.isPresent() / .get()
  • use: orElse() / orElseGet() / orElseThrow()
• Optional.filter() predicate
• Optional.ifPresent(): (<> isPresent) executes lambda if present
• other methods
  • empty()
  • of()
  • flatMap()
  • ...
• stream of Optional: .filter(Optional::isPresent).map(Optional::get).collect() -- filters present Optionals & extract values

misuses:

• simple nullchecks - avoid Optional.isNullable. chainsgh
• too complex constucts: Optional chains should be avoided
• Optional.get() "attractive nuisance" -- will be deprecated
• do not use Optional for
  • fields
  • method parameters
  • collections
  • replacing every null
• Optional adds extra objects -- check performance issues
• no identity-sensitive operations (e.g. serialization)

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A Crash Course in Modern Hardware

Cliff Click

• classic Von Neumann Architecture
• throughput / core +10% / year (single-threaded)
• CISC: easier to program, but harder to optimize (pagefaults)
• RISC: simpler, but faster execution
• walls:
  • power wall
  • ILP wall (branch prediction, speculative execution)
    • pipelining
      • better throughput, but latency remains
    • cache misses: stall -- performance = cache misses
    • branch predictions: 95% success
    • Itanium: static ILP: not much gain for huge effort
    • x86: limited by cache misses / branch mispredicts
    • locality is critical
  • memory wall
    • memory is larger, but latency is still high (DRAM)
    • SRAM for caches
      • requires data locality
      • cache layers
    • "memory is the new disk"
    • faster memory
      • relax coherency constraints
      • better throughput
  • speed of light
• flat clock rates (15y)
  • hyper-threading: same limits (cache misses)
  • more cores
    • challenges:
      • chips reorder
      • concurrency is hard
      • immutable data
      • missing toolsets

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The ISS position in real time on my mobile in less than 15mn ? Yes, we can.

Audrey Neveu

• api.open-notify.org
• ionic + cordova
• server-sent events: push technology: text-only
  • streamdata.io for streaming the server-sent-events
  • JSON-patch RFC-6902 for changes demo
• ionic start iss.io maps (=template)
• ionic serve --lab
• bower.json --> bower install

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graph databases and the "panama papers"

Stefan Armbruster

panama papers: 2,6 TB data

• 3 million files
• tools
  • Nuix OCR
  • icij extract for metadata extraction: https://github.com/ICIJ/extract
  • blacklight (opensource collaboration tool: http://projectblacklight.org/)
  • db
    • solr
    • redis
    • neo4j https://neo4j.com/
  • linkurious visualisation http://linkurio.us/ (commercial)

property graph model

• nodes: entities (can have name/value properties
• relationships: type + direction (=semantic)

neo4j usecases

• internal
  • network / it operations
  • data management
• customer facing
  • real-time recommendations
  • graph based search
  • identity/access management

neo4j:

• graph database -- easy to draw structure
• solves relational pains (logical vs table model)
• open source
• easy to use
• ACID
• scalable (3.1)
• syntax
  • patterns: (:Person{name:"Dan"})-:KNOWS>(:Person{name:"an"})
  • clauses CREATE / MERGE / SET/DELETE..
  • MATCH > WHERE <>
    • ORDER BY <>
    • paginationSKIP / LIMIT
  • LOAD CSV
• demo

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A JVM does That?

Cliff Click

 services -- "Virtual"

• high quality GC
• high quality machine code gen
• uniform threading / memory model
• type safety
• ...

Illusion:

• infinite mem -- gc pauses
  • jvm optimizes
• byte code is fast:
  • JIT brings back expected cost model (gcc -O2 level)
  • JIT requires profiling
• virtual calls are slow: java makes them fast
  • inline caches
• partial programs are fast: requires deoptimization, reprofile, reJIT
• consisten memory model: every machine has different memory models -- JVM handles this
• consistent thread model: JVM imporves locking etc
• Locks are fast
• quick time access: difficult on hardware / multiple threads *
  • gettimeofday in java

wishes for the future:

• tail calls
• Integer as cheap as int
• BigInteger as cheap as int
• atomic multi-address update (software transactional memory)
• thread priorities: on linux -- only as root
• finalizers: "eventually" runs -- might be never (no timeliness guarantees)
• soft/phantom refs: difficult to maintain in GC