Daily Archives: October 23, 2018

[2018 oracle code one] hands on lab JNoSQL

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Hands on Lab: Eclipse JNoSQL: One API to Many NoSQL Databases

Instructors: Leonardo Lima, Otavio Santana, Senior Software Engineer, Hillmer Chona, Patricia Uribe & Jonathan Vila Lopez

For more blog posts, see The Oracle Code One table of contents

Lab URL: https://github.com/JNOSQL/oc1-hands-on-2018

Overview of NoSQL

  • No fixed data structure
  • not ACID
  • BASE -Basically Available, Soft State, Eventual consistency
  • Five types
    • key/value – Redis, Hazelcast, Couchbase
    • column family – Hbase, Cassandra
    • document – Couchbase, MongoDB, Riak
    • graph – Neo4J
    • multi-model – OrientDB, Couchbase
  • From most scalable/least complex to least scalable/most complex – Key/value, column family, document, graph

JNoSQL

  • First Jakarta EE specification
  • Mapping API – Artemis
    • Heavily based on annotation
    • “Query by” methods
    • Inject DocumentTemplate – has CRUD methods
  • Communication API – Diana
  • Trying to replicate JDBC/JPA for NoSQL
  • Traditionally, use different API for each NoSQL type
    • BaseDocument
    • Document
    • JsonObject
    • ODocument
  • DocumentEntity/Document – for all the types
  • Working on for 2 years
  • Almost up to 1.0 version
  • Configuration is one json file

My take: I like that they brought/shared their own wifi. Good overview at the beginning. I think I missed the point of the instructions at first. It felt too freeform. But then it made sense once they started explaining the code. So either it assumed knowledge or I thought we were doing something else. (I did get it to work; I just thought we were supposed to be doing something else.) Also, there was an instructor for each 1-2 attendees. Every time I went to do something (email, Slack, pull request), someone asked me if I needed help. I was waiting for Maven/Docker, not being idle! Also, not their fault, but the improvised lab room had sun blocking the screen. Overall, I enjoyed the lab. The second exercise clicked because I understood what we were doing!

[2018 oracle code one] beyond git add/commit/push

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Beyond git add/commit/push
Speaker: Jorge Vargas and Victor Orozco
@edivargas and @tuxtor

Full deck: http://www.jorgevargas.mx/wp-content/uploads/2018/10/Git-SCM-en-v5.pdf

For more blog posts, see The Oracle Code One table of contents

Review

  • add – puts in to staging area (from working directory)
  • commit – puts in local repo
  • push – puts in remote repo
  • reset hash – override working directory with local repo
  • fetch – get from remote repo to local repo
  • pull – fetch + merging into your local branch
  • clone – get from remote repo to working dir

Workflow

  • select a workflow – varies by project, but all team members should know what using
  • Common workflows
    • Centralized – all commits to master. Usually for new git users.
    • Feature branch – do feature in a branch and then merge in.
    • Gitflow – do changes in branch and merge into develop. Then merge development into master. Only commit to master for hotfixes or when develop ready for release
    • Forking – copy of repo and merge in
  • Recommendations
    • No one workflow to rule them all.
    • Code in master should be complete and functional at all times
    • Create short lived branches
    • Use meaningful names for branches

Advanced Git commands

  • stash – a quick save of your working directory

Demo

  • git init – to create repo
  • git status – showed file in staging area
  • git commit – add file
  • Edit .gitignore – to omit .class files
  • git log – see actual commit
  • git log –oneline –graph –all – list commits one line per commit so easier to read. Shows which branch the change is in
  • git checkout -b newBranch – create new branch and switch to it
  • git branches – list all branches
  • git checkout master – switch to master
  • git checkout -b branch2 – create a second branch off master
  • git merge newBranch – first merge smooth
  • git merge branch2 – created merge conflict. Fix manually
  • git branch -d newBranch – delete branch

My take: I had trouble understanding their accents at first, but then it got easier. The content itself was good. I was also a little distracted getting ready for my session next. I like that they did a live demo. I thought the content was going to be more advanced. The mention of stash was a good one. But then the demo was easy. To be fair, a bunch of people in the room didn’t raise their hands for using git. They got to the advanced part right when they ran out of time. I look forward to reading the rest of the deck at least.

 

 

[2018 oracle code one] how to program a quantum computer

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You’re thinking too classically – how to program a quantum computer
Speaker: Tim Ellison
IBM

For more blog posts, see The Oracle Code One table of contents

General

  • When reach maturity of computers have today, will significantly outperform today’s classical computers
  • Need quantum computer to model quantum mechanics

Classical computers

  • Classical data and logic representation – data encoding (binary/ascii), logic gates (binary), computing circuits (built out of logic gates)
  • Need resilient bit store, data representation and algorithms. Don’t think about it much because data is reliable
  • Some problems are hard/not a good fit
    • Traveling salesman – 10 cities is 1.8 million routes. 20 cities is 1 billion billion routes
    • Optimizations (ex: minimize wastage cutting wood)- requires starting with a guess and trying all options
    • Modelling molecutes (simulate electron interactions – 25 electrons is laptop sized problems. 43 electrons ins Titan supercomputer
    • Modeling caffeine is impossible on today’s computers. But could represent in 160 quantum bits. And pharmaceuticals are far more complicated.

Quantum

  • Qubit in both 0 and 1 state at same time. Superposition
  • Collapses to a value when observe.
  • Can influence probability of it being a 0 or 1
  • Combine qubits to cause correlation of random results. Quantum entanglement “causes” both “linked” qubits to git save values.
  • Call experiments (vs programs) for quantum because results not deterministic
  • Power doubles every time add qubit.
  • 275 qubits is more states than number of atoms in universe
  • Fast to factor prime numbers using Shor’s algorithm [watch out security!]
  • Expect quantum computers to be used – chemistry, AI (classification, machine learning, linear algebra), financial services (portfolio optimization, scenario analysis, pricing)
  • Built with ions, photons, superconducting circuits.

Demo

https://quantumexperience.ng.bluemix.net/qx

  • 5 qubits
  • Get 21 units (since free, it is rate limited.) Once experiment completed, get results back
  • Can run on real quantum computer or on simulator
  • Result gives you the probability of different results
  • Shows openqasm. A quantum assembly language
  • H gate puts into superposition state
  • Large program runs in O(square root of n) vs O(n^2) complexity

Resources

  • Python API: https://github.com/QISKit – build, compile/transpile and execute
  • Run experiments: https://quantumexperience.ng.bluemix.net/qx

Journey

  • Science is well understood
  • Machines currently error prone. Nothing can do on quantum that can’t do on classical (yet)
  • Quantum Advantage – being able to benefit from quantum
  • Prediction: less than 5 years for chemistry. 10-15 years for breaking cryptography
  • Starting to build data centers in Poughkeepsie (upstate NY)

My take: The basics of this I’ve heard before. It was cool seeing IBM’s experiment generator used. It’ll be interesting seeing where this goes. The speaker said this was normally a 2 hour talk. I liked the part about applications of quantum and how they are built. I also liked seeing the assembly and graphical code.