Google Cloud SQL

Another xing bang API from the boyz in Mountain View. (entry by invite only) But it is free and you can test your stuff on a MySQL db =10 GB

Database as a service ? (Maybe)— while Amazon was building fires (and Fire)

—————————————————————–

https://code.google.com/apis/sql/index.html

What is Google Cloud SQL?

Google Cloud SQL is a web service that provides a highly available, fully-managed, hosted SQL storage solution for your App Engine applications.

What are the benefits of using Google Cloud SQL?

You can access a familiar, highly available SQL database from your App Engine applications, without having to worry about provisioning, management, and integration with other Google services.

How much does Google Cloud SQL cost?

We will not be billing for this service in 2011. We will give you at least 30 days’ advance notice before we begin billing in the future. Other services such as Google App Engine, Google Cloud Storage etc. that you use with Google Cloud SQL may have their own payment terms, and you need to pay for them. Please consult their documentation for details.

Currently you are limited to the three instance sizes. What if I need to store more data or need better performance?

In the Limited Preview period, we only have three sizes available. If you have specific needs, we would like to hear from you on our google-cloud-sqldiscussion board.

When is Google Cloud SQL be out of Limited Preview?

We are working hard to make the service generally available.We don’t have a firm date that we can announce right now.

Do you support all the features of MySQL?

In general, Google Cloud SQL supports all the features of MySQL. The following are lists of all the unsupported features and notable differences that Google Cloud SQL has from MySQL.

Unsupported Features:

  • User defined functions
  • MySql replication

Unsupported MySQL statements:

  • LOAD DATA INFILE
  • SELECT ... INTO OUTFILE
  • SELECT ... INTO DUMPFILE
  • INSTALL PLUGIN .. SONAME ...
  • UNINSTALL PLUGIN
  • CREATE FUNCTION ... SONAME ...

Unsupported SQL Functions:

  • LOAD_FILE()

Notable Differences:

  • If you want to import databases with binary data into your Google Cloud SQL instance, you must use the --hex-blob option with mysqldump.Although this is not a required flag when you are using a local MySQL server instance and the MySQL command line, it is required if you want to import any databases with binary data into your Google Cloud SQL instance. For more information, see Importing Data.
How large a database can I use with Google Cloud SQL?
Currently, in this limited preview period, your database instance must be no larger than 10GB.
How can I be notified when there are any changes to Google Cloud SQL?
You can sign up for the sql-announcements forum where we post announcements and news about the Google Cloud SQL.
How can I cancel my Google Cloud SQL account?
To remove all data from your Google Cloud SQL account and disable the service:

  1. Delete all your data. You can remove your tables, databases, and indexes using the drop command. For more information, see SQL DROP statement.
  2. Deactivate the Google Cloud SQL by visiting the Services pane and clicking the On button next to Google Cloud SQL. The button changes from Onto Off.
How do I report a bug, request a feature, or ask a question?
You can report bugs and request a feature on our project page.You can ask a question in our discussion forum.

Getting Started

Can I use languages other than Java or Python?
Only Java and Python are supported for Google Cloud SQL.
Can I use Google Cloud SQL outside of Google App Engine?
The Limited Preview is primarily focused on giving Google App Engine customers the ability to use a familiar relational database environment. Currently, you cannot access Google Cloud SQL from outside Google App Engine.
What database engine are we using in the Google Cloud SQL?
MySql Version 5.1.59
Do I need to install a local version of MySQL to use the Development Server?
Yes.

Managing Your Instances

Do I need to use the Google APIs Console to use Google Cloud SQL?
Yes. For basic tasks like granting access control to applications, creating instances, and deleting instances, you need to use the Google APIs Console.
Can I import or export specific databases?
No, currently it is not possible to export specific databases. You can only export your entire instance.
Do I need a Google Cloud Storage account to import or export my instances?
Yes, you need to sign up for a Google Cloud Storage account or have access to a Google Cloud Storage account to import or export your instances. For more information, see Importing and Exporting Data.
If I delete my instance, can I reuse the instance name?
Yes, but not right away. The instance name is reserved for up to two months before it can be reused.

Tools & Resources

Can I use Django with Google Cloud SQL?
No, currently Google Cloud SQL is not compatible with Django.
What is the best tool to use for interacting with my instance?
There are a variety of tools available for Google Cloud SQL. For executing simple statements, you can use the SQL prompt. For executing more complicated tasks, you might want to use the command line tool. If you want to use a tool with a graphical interface, the SQuirrel SQL Client provides an interface you can use to interact with your instance.

Common Technical Questions

Should I use InnoDB for my tables?
Yes. InnoDB is the default storage engine in MySQL 5.5 and is also the recommended storage engine for Google Cloud SQL. If you do not need any features that require MyISAM, you should use InnoDB. You can convert your existing tables using the following SQL command, replacing tablename with the name of the table to convert:

ALTER tablename ENGINE = InnoDB;

If you have a mysqldump file where all your tables are in MyISAM format, you can convert them by piping the file through a sed script:

mysqldump --databases database_name [-u username -p  password] --hex-blob database_name | sed 's/ENGINE=MyISAM/ENGINE=InnoDB/g' > database_file.sql

Warning: You should not do this if your mysqldump file contains the mysql schema. Those files must remain in MyISAM.

Are there any size or QPS limits?
Yes, the following limits apply to Google Cloud SQL:

Resource Limits from External Requests Limits from Google App Engine
Queries Per Second (QPS) 5 QPS No limit
Maximum Request Size 16 MB
Maximum Response Size 16 MB

Google App Engine Limits

Google App Engine applications are also subject to additional Google App Engine quotas and limits. Requests from Google App Engine applications to Google Cloud SQL are subject to the following time limits:

  • All database requests must finish within the HTTP request timer, around 60 seconds.
  • Offline requests like cron tasks have a time limit of 10 minutes.
  • Backend requests to Google Cloud SQL have a time limit of 10 minutes.

App Engine-specific quotas and access limits are discussed on the Google App Engine Quotas page.

Should I use Google Cloud SQL with my non-High Replication App Engine application?
We recommend that you use Google Cloud SQL with High Replication App Engine applications. While you can use use Google Cloud SQL with applications that do not use high replication, doing so might impact performance.
Source-
https://code.google.com/apis/sql/faq.html#supportmysqlfeatures

Google Cloud Connect

 

Interestingly a Google Plugin to share Microsoft Office on the Cloud.

Google Cloud Connect is a plug-in for Microsoft Office® 2003, 2007, and 2010 that lets you share and edit Microsoft Word, PowerPoint, and Excel documents simultaneously with other people in your organization. You get the collaboration benefits of Google Docs, while still using Microsoft Office.

http://tools.google.com/dlpage/cloudconnect

Google Cloud Connect for Microsoft Office

Google Cloud Connect for Microsoft Office brings collaborative multi-person editing to the familiar Microsoft® Office experience. You can share, backup, and simultaneously edit Microsoft Word, PowerPoint®, and Excel® documents with coworkers.

Watch the videos below to learn how Google Cloud Connect teaches your old docs new tricks.

Learn how Cloud Connect helped Mazda Raceway Laguna Seca (English only)

Help and information for users
Help and information for administrators

Download Google Cloud Connect

It’s free and downloads in seconds.

Requirements:

  • Windows XP with .NET Framework 2.0, Windows Vista, or Windows 7
  • Microsoft Office 2003, Office 2007, or Office 2010

PMML Plugin for Greenplum now available

Predictive Model Markup Language
Image via Wikipedia

From a press release from Zementis.

 

, the Universal PMML Plug-in for in-database scoring. Available now for the EMC Greenplum Database, a high-performance massively parallel processing (MPP) database, the plug-in leverages the Predictive Model Markup Language (PMML) to execute predictive models directly within EMC Greenplum, for highly optimized in-database scoring.

Universal PMML Plug-in

Developed by the Data Mining Group (DMG), PMML is supported by all major data mining vendors, e.g., IBM SPSS, SAS, Teradata, FICO, STASTICA, Microstrategy, TIBCO and Revolution Analytics as well as open source tools like R, KNIME and RapidMiner. With PMML, models built in any of these data mining tools can now instantly be deployed in the EMC Greenplum database. The net result is the ability to leverage the power of standards-based predictive analytics on a massive scale, right where the data resides.

“By partnering with Zementis, a true PMML innovator, we are able to offer a vendor-agnostic solution for moving enterprise-level predictive analytics into the database execution environment,” said Dr. Steven Hillion, Vice President of Analytics at EMC Greenplum. “With Zementis and PMML, the de-facto standard for representing data mining models, we are eliminating the need to recode predictive analytic models in order to deploy them within our database. In turn, this enables an analyst to reduce the time to insight required in most businesses today.”

Want to learn more?
 

To learn more about how the EMC Greenplum Database and the Universal PMML Plug-in work together, feel free to:

  1. Visit the PMML Plug-in product page
  2. Download the white paper

The Universal PMML Plug-in for the EMC Greenplum Database is available now. Contact us today for more information.

Michael Zeller, CEO, Zementis

 

 

The Latest GUI for R- BioR

Once more a spanking new shiny software –

Bio7 is a integrated development environment for ecological modelling based on the Rich-Client-Platformconcept of the Java IDE Eclipse. The Bio7 platform contains several perspectives which arrange several views for a special purpose useful for the development and analysis of ecological models. One special perspective bundles a feature rich GUI (Graphical User Interface) for the statistical software R.
For the bidirectional communication between Java and R the Rserve application is used (as a backend to evaluate R code and transfer data from and to Java).
The Bio7 R perspective (see figure below) is divided into a R-Shell view on the left side (conceptual the R side) and a Table view on the right side (conceptual the Java side).
Data can be imported to a spreadsheet, edited and then transferred to the R workspace. Vice versa data from R can be transferred to a sheet of the Table view and then exported e.g. to an Excel or OpenOffice file.

and

General:

Built upon Eclipse 3.6.1.

Now works with the latest Java version! (Windows version bundled with the latest JRE release).

Removed the Soil perspective (now soils can be modeled with ImageJ (float precision). Active images can be displayed in the 3D discrete view (new example available).

Removed the database perspective and the plant layer. You can now built any discrete models without any plant layer.

Removed several controls in the Control view. Added the “Custom Controls” view. In addition ported the Swing component of the Time panel to Swt.

Deleted the avi to swf converter in the ImageJ menu.

Now patterns can be saved with opened Java editor source. If this file is reopened and dragged on Bio7 the pattern is loaded, the source is compiled and the setup method (if available) is executed. In this way model files can be used for presentations ->drag, setup and run. The save actions are located in the Speadsheet view toolbar.

More options available to disable panel painting and recording of values (if not needed for speed!).

New Setup button in the toolbar of Bio7 to trigger a compiled setup method if available.

Removed the load and save pattern buttons from the toolbar of Bio7. Discrete patterns can now be stored with the available action in the spreadsheet view menu.

New P2 Update Manager available in Bio7.

Updated the Janino Compiler.

New HTML perspective added with a view which embeds the TinyMC editor.

New options to disable painting operations for the discrete panels.

New option to explicitly enable scripts at startup (for a faster startup).

Quadgrid (Hexgrid)

Only states are now available which can be created in the “Spreadsheet” view menu easily. Patterns can be stored and restored as usual but are now stored in an *.exml file.

New method to transfer the quadgrid pattern as a matrix to R.

New method to transfer the population data of all quadgrid states to R.

ImageJ:

Update to the latest version (with additional fixes).

Fixed a bug to rename the image.

Thumbnail browser can now open images recursevely(limited to 1000 pics), the magnifiyng glass can be disabled, too.

Plugins can be installed dynamically with a drag and drop operation on the ImageJ view or toolbar (as known from ImageJ).

Installed plugins now extend the plugin menu as submenus or subsubmenus (not finished yet!).

Plugins can now be created with the Java editor. New Bio7 Wizard available to create a plugin template.

Compiled Java files can be added to a *.jar file with a new available action in the Navigator view (if you rightclick on the files in the Navigator). In this way ImageJ plugins can be packaged in a *.jar.

Floweditor:

Fixed a repaint bug in the debug mode of a flow (now draws correctly the active shape in the flow).

Resize with Strg+Scrollwheel works again.

Comments with more than one line works again.

New Test action to verify connections in a flow.

Debug mode now shows all executed Shapes.

Integrated more default tests (for the verification of a regular flow).

A mouse-click now deletes colored shapes in a flow (e.g. in debug mode).

Points panel:

Integrated (dynamic) Voronoi, Delauney visualization (with area and clip to rectangle action).

Points coordinates can now be set in double precision.

Transfer of point coordinates to R now in double precision.

Bio7 Table:

New import and export of Excel 2007 OOXML.

Row headers can now be resized with the mouse device.

R:

Updated R (2.12.1) and Rserve (0.6.3) to the latest version.

New help action in the R-Shell view.

New action to display help for R specific commands in the embedded Bio7 browser (which opens automatically).

New Key actions to copy the selected variable names to the expression dialog (c=cocatenate (+), a=add (,)).

New action to transfer character or numeric vectors horizontally or vertically in an opened spread (Table view) at selection coordinates.

Empty spaces in the filepath are now allowed under Windows if Rserve is started with a system shell or the RGUI (for the tempfile select a location in the Preferences dialog which is writeable) is started.This works also for the RGUI action.

Improved the search for the “Install packages” action (option “Case Sensitive” added).

API:

New API methods available!

And:

Many fixes since the last version!

 

Installation

Important information:

A certain firewall software can corrupt the Bio7 *.zip file (as well as other files).
Please ensure that you have downloaded a functioning Bio7 1.5 version. In addition it is also reported that a certain antivirus software detects the bundled R software (on Windows) as malware. Often the R specific “open.exe” is detected as malware. Please use a different scanner to make sure that the software is not infected if you have any doubts. For more details see:

http://r.789695.n4.nabble.com/trojan-at-current-development-version-td3244348.html

 

Using R from other Software

Bridge to R for WPS

http://www.minequest.com/Bridge2R.html

SAS/IML Interface to R

http://www.sas.com/technologies/analytics/statistics/iml/index.html

Official Screenshot-

RapidMiner Extension to R

https://rapid-i.com/content/view/202/206/lang,en/#r

(UN)Official Screenshot-

IBM SPSS plugin for R

https://www.spss.com/software/statistics/developer/

and

https://www.spss.com/devcentral/index.cfm?pg=rresources

Tutorial-

https://sites.google.com/site/r4statistics/running-r-from-spss

http://rwiki.sciviews.org/doku.php?id=tips:callingr:spss

(UN)official Screenshot

Knime

http://www.knime.org/downloads/extensions

Official Screenshot-

Oracle Data Miner

http://www.oracle.com/technetwork/database/options/odm/odm-r-integration-089013.html

Official Screenshot-

JMP

http://jmp.com/software/jmp9/keyfeatures.shtml

and

http://www.jmp.com/applications/analytical_apps/

Tutorial

http://blogs.sas.com/jmp/index.php?/archives/298-JMP-Into-R!.html

Screenshot-

Protovis a graphical toolkit for visualization

I just found about a new data visualization tool called Protovis http://vis.stanford.edu/protovis/ex/

Protovis composes custom views of data with simple marks such as bars and dots. Unlike low-level graphics libraries that quickly become tedious for visualization, Protovis defines marks through dynamic properties that encode data, allowing inheritancescales and layouts to simplify construction.

Protovis is free and open-source and is a Stanford project. It has been used in web interface R Node (which I will talk later )

http://squirelove.net/r-node/doku.php

Conventional

While Protovis is designed for custom visualization, it is still easy to create many standard chart types. These simpler examples serve as an introduction to the language, demonstrating key abstractions such as quantitative and ordinal scales, while hinting at more advanced features, including stack layout.

Custom

Many charting libraries provide stock chart designs, but offer only limited customization; Protovis excels at custom visualization design through a concise representation and precise control over graphical marks. These examples, including a few recreations of unusual historical designs, demonstrate the language’s expressiveness.

 

 

Try Protovis today 🙂 http://vis.stanford.edu/protovis/

It uses JavaScript and SVG for web-native visualizations; no plugin required (though you will need a modern web browser)! Although programming experience is helpful, Protovis is mostly declarative and designed to be learned by example.

R Commander Plugins-20 and growing!

First graphical user interface in 1973.
Image via Wikipedia
R Commander Extensions: Enhancing a Statistical Graphical User Interface by extending menus to statistical packages

R Commander ( see paper by Prof J Fox at http://www.jstatsoft.org/v14/i09/paper ) is a well known and established graphical user interface to the R analytical environment.
While the original GUI was created for a basic statistics course, the enabling of extensions (or plug-ins  http://www.r-project.org/doc/Rnews/Rnews_2007-3.pdf ) has greatly enhanced the possible use and scope of this software. Here we give a list of all known R Commander Plugins and their uses along with brief comments.

  1. DoE – http://cran.r-project.org/web/packages/RcmdrPlugin.DoE/RcmdrPlugin.DoE.pdf
  2. doex
  3. EHESampling
  4. epack- http://cran.r-project.org/web/packages/RcmdrPlugin.epack/RcmdrPlugin.epack.pdf
  5. Export- http://cran.r-project.org/web/packages/RcmdrPlugin.Export/RcmdrPlugin.Export.pdf
  6. FactoMineR
  7. HH
  8. IPSUR
  9. MAc- http://cran.r-project.org/web/packages/RcmdrPlugin.MAc/RcmdrPlugin.MAc.pdf
  10. MAd
  11. orloca
  12. PT
  13. qcc- http://cran.r-project.org/web/packages/RcmdrPlugin.qcc/RcmdrPlugin.qcc.pdf and http://cran.r-project.org/web/packages/qcc/qcc.pdf
  14. qual
  15. SensoMineR
  16. SLC
  17. sos
  18. survival-http://cran.r-project.org/web/packages/RcmdrPlugin.survival/RcmdrPlugin.survival.pdf
  19. SurvivalT
  20. Teaching Demos

Note the naming convention for above e plugins is always with a Prefix of “RCmdrPlugin.” followed by the names above
Also on loading a Plugin, it must be already installed locally to be visible in R Commander’s list of load-plugin, and R Commander loads the e-plugin after restarting.Hence it is advisable to load all R Commander plugins in the beginning of the analysis session.

However the notable E Plugins are
1) DoE for Design of Experiments-
Full factorial designs, orthogonal main effects designs, regular and non-regular 2-level fractional
factorial designs, central composite and Box-Behnken designs, latin hypercube samples, and simple D-optimal designs can currently be generated from the GUI. Extensions to cover further latin hypercube designs as well as more advanced D-optimal designs (with blocking) are planned for the future.
2) Survival- This package provides an R Commander plug-in for the survival package, with dialogs for Cox models, parametric survival regression models, estimation of survival curves, and testing for differences in survival curves, along with data-management facilities and a variety of tests, diagnostics and graphs.
3) qcc -GUI for  Shewhart quality control charts for continuous, attribute and count data. Cusum and EWMA charts. Operating characteristic curves. Process capability analysis. Pareto chart and cause-and-effect chart. Multivariate control charts
4) epack- an Rcmdr “plug-in” based on the time series functions. Depends also on packages like , tseries, abind,MASS,xts,forecast. It covers Log-Exceptions garch
and following Models -Arima, garch, HoltWinters
5)Export- The package helps users to graphically export Rcmdr output to LaTeX or HTML code,
via xtable() or Hmisc::latex(). The plug-in was originally intended to facilitate exporting Rcmdr
output to formats other than ASCII text and to provide R novices with an easy-to-use,
easy-to-access reference on exporting R objects to formats suited for printed output. The
package documentation contains several pointers on creating reports, either by using
conventional word processors or LaTeX/LyX.
6) MAc- This is an R-Commander plug-in for the MAc package (Meta-Analysis with
Correlations). This package enables the user to conduct a meta-analysis in a menu-driven,
graphical user interface environment (e.g., SPSS), while having the full statistical capabilities of
R and the MAc package. The MAc package itself contains a variety of useful functions for
conducting a research synthesis with correlational data. One of the unique features of the MAc
package is in its integration of user-friendly functions to complete the majority of statistical steps
involved in a meta-analysis with correlations. It uses recommended procedures as described in
The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).

A query to help for ??Rcmdrplugins reveals the following information which can be quite overwhelming given that almost 20 plugins are now available-

RcmdrPlugin.DoE::DoEGlossary
Glossary for DoE terminology as used in
RcmdrPlugin.DoE
RcmdrPlugin.DoE::Menu.linearModelDesign
RcmdrPlugin.DoE Linear Model Dialog for
experimental data
RcmdrPlugin.DoE::Menu.rsm
RcmdrPlugin.DoE response surface model Dialog
for experimental data
RcmdrPlugin.DoE::RcmdrPlugin.DoE-package
R-Commander plugin package that implements
design of experiments facilities from packages
DoE.base, FrF2 and DoE.wrapper into the
R-Commander
RcmdrPlugin.DoE::RcmdrPlugin.DoEUndocumentedFunctions
Functions used in menus
RcmdrPlugin.doex::ranblockAnova
Internal RcmdrPlugin.doex objects
RcmdrPlugin.doex::RcmdrPlugin.doex-package
Install the DOEX Rcmdr Plug-In
RcmdrPlugin.EHESsampling::OpenSampling1
Internal functions for menu system of
RcmdrPlugin.EHESsampling
RcmdrPlugin.EHESsampling::RcmdrPlugin.EHESsampling-package
Help with EHES sampling
RcmdrPlugin.Export::RcmdrPlugin.Export-package
Graphically export objects to LaTeX or HTML
RcmdrPlugin.FactoMineR::defmacro
Internal RcmdrPlugin.FactoMineR objects
RcmdrPlugin.FactoMineR::RcmdrPlugin.FactoMineR
Graphical User Interface for FactoMineR
RcmdrPlugin.IPSUR::IPSUR-package
An IPSUR Plugin for the R Commander
RcmdrPlugin.MAc::RcmdrPlugin.MAc-package
Meta-Analysis with Correlations (MAc) Rcmdr
Plug-in
RcmdrPlugin.MAd::RcmdrPlugin.MAd-package
Meta-Analysis with Mean Differences (MAd) Rcmdr
Plug-in
RcmdrPlugin.orloca::activeDataSetLocaP
RcmdrPlugin.orloca: A GUI for orloca-package
(internal functions)
RcmdrPlugin.orloca::RcmdrPlugin.orloca-package
RcmdrPlugin.orloca: A GUI for orloca-package
RcmdrPlugin.orloca::RcmdrPlugin.orloca.es
RcmdrPlugin.orloca.es: Una interfaz grafica
para el paquete orloca
RcmdrPlugin.qcc::RcmdrPlugin.qcc-package
Install the Demos Rcmdr Plug-In
RcmdrPlugin.qual::xbara
Internal RcmdrPlugin.qual objects
RcmdrPlugin.qual::RcmdrPlugin.qual-package
Install the quality Rcmdr Plug-In
RcmdrPlugin.SensoMineR::defmacro
Internal RcmdrPlugin.SensoMineR objects
RcmdrPlugin.SensoMineR::RcmdrPlugin.SensoMineR
Graphical User Interface for SensoMineR
RcmdrPlugin.SLC::Rcmdr.help.RcmdrPlugin.SLC
RcmdrPlugin.SLC: A GUI for slc-package
(internal functions)
RcmdrPlugin.SLC::RcmdrPlugin.SLC-package
RcmdrPlugin.SLC: A GUI for SLC R package
RcmdrPlugin.sos::RcmdrPlugin.sos-package
Efficiently search R Help pages
RcmdrPlugin.steepness::Rcmdr.help.RcmdrPlugin.steepness
RcmdrPlugin.steepness: A GUI for
steepness-package (internal functions)
RcmdrPlugin.steepness::RcmdrPlugin.steepness
RcmdrPlugin.steepness: A GUI for steepness R
package
RcmdrPlugin.survival::allVarsClusters
Internal RcmdrPlugin.survival Objects
RcmdrPlugin.survival::RcmdrPlugin.survival-package
Rcmdr Plug-In Package for the survival Package
RcmdrPlugin.TeachingDemos::RcmdrPlugin.TeachingDemos-package
Install the Demos Rcmdr Plug-In