Creating Pages on Google Plus for some languages

So I decided to create Pages on Google Plus for my favorite programming languages.

a programming language that lets you work more quickly and integrate your systems more effectively

Add to circles

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Ajay Ohri

Ajay Ohri's profile photo

Ajay Ohri  –
Ajay Ohri shared a Google+ page with you.
Structured Query Language
Leading statistical language since 1960’s especially in sociology and market research
The leading statistical language in the world
The leading statistical language since 1970’s

Python

https://plus.google.com/107930407101060924456/posts

 

These are in accordance with Google’s Policies http://www.google.com/intl/en/+/policy/pagesterm.html  Continue reading “Creating Pages on Google Plus for some languages”

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

Use R for Business- Competition worth $ 20,000 #rstats

All you contest junkies, R lovers and general change the world people, here’s a new contest to use R in a business application

http://www.revolutionanalytics.com/news-events/news-room/2011/revolution-analytics-launches-applications-of-r-in-business-contest.php

REVOLUTION ANALYTICS LAUNCHES “APPLICATIONS OF R IN BUSINESS” CONTEST

$20,000 in Prizes for Users Solving Business Problems with R

 

PALO ALTO, Calif. – September 1, 2011 – Revolution Analytics, the leading commercial provider of R software, services and support, today announced the launch of its “Applications of R in Business” contest to demonstrate real-world uses of applying R to business problems. The competition is open to all R users worldwide and submissions will be accepted through October 31. The Grand Prize winner for the best application using R or Revolution R will receive $10,000.

The bonus-prize winner for the best application using features unique to Revolution R Enterprise – such as itsbig-data analytics capabilities or its Web Services API for R – will receive $5,000. A panel of independent judges drawn from the R and business community will select the grand and bonus prize winners. Revolution Analytics will present five honorable mention prize winners each with $1,000.

“We’ve designed this contest to highlight the most interesting use cases of applying R and Revolution R to solving key business problems, such as Big Data,” said Jeff Erhardt, COO of Revolution Analytics. “The ability to process higher-volume datasets will continue to be a critical need and we encourage the submission of applications using large datasets. Our goal is to grow the collection of online materials describing how to use R for business applications so our customers can better leverage Big Analytics to meet their analytical and organizational needs.”

To enter Revolution Analytics’ “Applications of R in Business” competition Continue reading “Use R for Business- Competition worth $ 20,000 #rstats”

More fun on Google Plus

I have been posting cool stuff from my G+ stream almost since the social network got released so continuing the series of posts on great stuff I get in my Google Plus stream

1) Photographers are good sharers
Anna Rumiantseva's profile photoAnna Rumiantseva originally shared this post:
Photos from our recent trip to Santa Fe, NM. These are of Loretto Chapel which has the Miraculous Staircase. This staircase has a mystery to it has it is said to be built without nails by a carpenter who showed up after the sisters of the chapel prayed for 9 days. It took several months to be built by this carpenter who then left without pay and could not be found. The sisters believe it was St. Joseph himself that built the staircase and answered their prayers.
Please share if you like!
2) Cool Designer Retro Stuff
 the water cooler at my workplace.
3) Social Media Experts-
Jay Jaboneta's profile photoJay Jaboneta originally shared this post:
GMA Network launched an online campaign to raise awareness about the responsible use of social media, so please think before you click.

Jay Jaboneta changed his profile photo.

4) No you cant share gifs on Facebook
5)  Cool Art
Monica Rocha's profile photoMonica Rocha originally shared this post:
6) Toons
Rupesh Nandy's profile photoRupesh Nandy originally shared this post:
Birthdays – Then & Now
8) Geeks rock!
David Smith's profile photoDavid Smith originally shared this post:
Yet another instance of the Golden Ratio in Nature: Irene.
lastly 9) Digital art
Marcelo Almeida's profile photoMarcelo Almeida originally shared this post:
behind the smile

 

But Willie Nelson rules them all

Willie Nelson covers Coldplay. Sounds pretty good! This reminds me of Johnny Cash’s cover ofHurt. (Yes, this is a Chipotle ad. It’s still pretty cool.)
youtube.com – Coldplay’s haunting classic ‘The Scientist’ is performed by country music legend Willie Nelson

https://www.youtube-nocookie.com/v/aMfSGt6rHos?version=3&hl=en_US&rel=0

– see earlier posts at

  1. https://decisionstats.com/best-of-google-plus-week-1-top10/
  2. http://www.decisionstats.com/best-of-google-plus-week-2-top-10/
  3.  http://www.decisionstats.com/the-best-of-google-plus-week-3-top-10/
  4. http://www.decisionstats.com/funny-stuff-on-google-plus/
  5. http://www.decisionstats.com/fun-with-google-plus/
Warning- this and earlier post deals with cute memes that can take a lot of time and energy!

 

 

 

 

 

Using Google Fusion Tables from #rstats

But after all that- I was quite happy to see Google Fusion Tables within Google Docs. Databases as a service ? Not quite but still quite good, and lets see how it goes.

https://www.google.com/fusiontables/DataSource?dsrcid=implicit&hl=en_US&pli=1

http://googlesystem.blogspot.com/2011/09/fusion-tables-new-google-docs-app.html

 

But what interests me more is

http://code.google.com/apis/fusiontables/docs/developers_guide.html

The Google Fusion Tables API is a set of statements that you can use to search for and retrieve Google Fusion Tables data, insert new data, update existing data, and delete data. The API statements are sent to the Google Fusion Tables server using HTTP GET requests (for queries) and POST requests (for inserts, updates, and deletes) from a Web client application. The API is language agnostic: you can write your program in any language you prefer, as long as it provides some way to embed the API calls in HTTP requests.

The Google Fusion Tables API does not provide the mechanism for submitting the GET and POST requests. Typically, you will use an existing code library that provides such functionality; for example, the code libraries that have been developed for the Google GData API. You can also write your own code to implement GET and POST requests.

Also see http://code.google.com/apis/fusiontables/docs/sample_code.html

 

Google Fusion Tables API Sample Code

Libraries

SQL API

Language Library Public repository Samples
Python Fusion Tables Python Client Library fusion-tables-client-python/ Samples
PHP Fusion Tables PHP Client Library fusion-tables-client-php/ Samples

Featured Samples

An easy way to learn how to use an API can be to look at sample code. The table above provides links to some basic samples for each of the languages shown. This section highlights particularly interesting samples for the Fusion Tables API.

SQL API

Language Featured samples API version
cURL
  • Hello, cURLA simple example showing how to use curl to access Fusion Tables.
SQL API
Google Apps Script SQL API
Java
  • Hello, WorldA simple walkthrough that shows how the Google Fusion Tables API statements work.
  • OAuth example on fusion-tables-apiThe Google Fusion Tables team shows how OAuth authorization enables you to use the Google Fusion Tables API from a foreign web server with delegated authorization.
SQL API
Python
  • Docs List ExampleDemonstrates how to:
    • List tables
    • Set permissions on tables
    • Move a table to a folder
Docs List API
Android (Java)
  • Basic Sample ApplicationDemo application shows how to create a crowd-sourcing application that allows users to report potholes and save the data to a Fusion Table.
SQL API
JavaScript – FusionTablesLayer Using the FusionTablesLayer, you can display data on a Google Map

Also check out FusionTablesLayer Builder, which generates all the code necessary to include a Google Map with a Fusion Table Layer on your own website.

FusionTablesLayer, Google Maps API
JavaScript – Google Chart Tools Using the Google Chart Tools, you can request data from Fusion Tables to use in visualizations or to display directly in an HTML page. Note: responses are limited to 500 rows of data.

Google Chart Tools

External Resources

Google Fusion Tables is dedicated to providing code examples that illustrate typical uses, best practices, and really cool tricks. If you do something with the Google Fusion Tables API that you think would be interesting to others, please contact us at googletables-feedback@google.com about adding your code to our Examples page.

  • Shape EscapeA tool for uploading shape files to Fusion Tables.
  • GDALOGR Simple Feature Library has incorporated Fusion Tables as a supported format.
  • Arc2CloudArc2Earth has included support for upload to Fusion Tables via Arc2Cloud.
  • Java and Google App EngineODK Aggregate is an AppEngine application by the Open Data Kit team, uses Google Fusion Tables to store survey data that is collected through input forms on Android mobile phones. Notable code:
  • R packageAndrei Lopatenko has written an R interface to Fusion Tables so Fusion Tables can be used as the data store for R.
  • RubySimon Tokumine has written a Ruby gem for access to Fusion Tables from Ruby.

 

Updated-You can use Google Fusion Tables from within R from http://andrei.lopatenko.com/rstat/fusion-tables.R

 

ft.connect <- function(username, password) {
  url = "https://www.google.com/accounts/ClientLogin";
  params = list(Email = username, Passwd = password, accountType="GOOGLE", service= "fusiontables", source = "R_client_API")
 connection = postForm(uri = url, .params = params)
 if (length(grep("error", connection, ignore.case = TRUE))) {
 	stop("The wrong username or password")
 	return ("")
 }
 authn = strsplit(connection, "\nAuth=")[[c(1,2)]]
 auth = strsplit(authn, "\n")[[c(1,1)]]
 return (auth)
}

ft.disconnect <- function(connection) {
}

ft.executestatement <- function(auth, statement) {
      url = "http://tables.googlelabs.com/api/query"
      params = list( sql = statement)
      connection.string = paste("GoogleLogin auth=", auth, sep="")
      opts = list( httpheader = c("Authorization" = connection.string))
      result = postForm(uri = url, .params = params, .opts = opts)
      if (length(grep("<HTML>\n<HEAD>\n<TITLE>Parse error", result, ignore.case = TRUE))) {
      	stop(paste("incorrect sql statement:", statement))
      }
      return (result)
}

ft.showtables <- function(auth) {
   url = "http://tables.googlelabs.com/api/query"
   params = list( sql = "SHOW TABLES")
   connection.string = paste("GoogleLogin auth=", auth, sep="")
   opts = list( httpheader = c("Authorization" = connection.string))
   result = getForm(uri = url, .params = params, .opts = opts)
   tables = strsplit(result, "\n")
   tableid = c()
   tablename = c()
   for (i in 2:length(tables[[1]])) {
     	str = tables[[c(1,i)]]
   	    tnames = strsplit(str,",")
   	    tableid[i-1] = tnames[[c(1,1)]]
   	    tablename[i-1] = tnames[[c(1,2)]]
   	}
   	tables = data.frame( ids = tableid, names = tablename)
    return (tables)
}

ft.describetablebyid <- function(auth, tid) {
   url = "http://tables.googlelabs.com/api/query"
   params = list( sql = paste("DESCRIBE", tid))
   connection.string = paste("GoogleLogin auth=", auth, sep="")
   opts = list( httpheader = c("Authorization" = connection.string))
   result = getForm(uri = url, .params = params, .opts = opts)
   columns = strsplit(result,"\n")
   colid = c()
   colname = c()
   coltype = c()
   for (i in 2:length(columns[[1]])) {
     	str = columns[[c(1,i)]]
   	    cnames = strsplit(str,",")
   	    colid[i-1] = cnames[[c(1,1)]]
   	    colname[i-1] = cnames[[c(1,2)]]
   	    coltype[i-1] = cnames[[c(1,3)]]
   	}
   	cols = data.frame(ids = colid, names = colname, types = coltype)
    return (cols)
}

ft.describetable <- function (auth, table_name) {
   table_id = ft.idfromtablename(auth, table_name)
   result = ft.describetablebyid(auth, table_id)
   return (result)
}

ft.idfromtablename <- function(auth, table_name) {
    tables = ft.showtables(auth)
	tableid = tables$ids[tables$names == table_name]
	return (tableid)
}

ft.importdata <- function(auth, table_name) {
	tableid = ft.idfromtablename(auth, table_name)
	columns = ft.describetablebyid(auth, tableid)
	column_spec = ""
	for (i in 1:length(columns)) {
		column_spec = paste(column_spec, columns[i, 2])
		if (i < length(columns)) {
			column_spec = paste(column_spec, ",", sep="")
		}
	}
	mdata = matrix(columns$names,
	              nrow = 1, ncol = length(columns),
	              dimnames(list(c("dummy"), columns$names)), byrow=TRUE)
	select = paste("SELECT", column_spec)
	select = paste(select, "FROM")
	select = paste(select, tableid)
	result = ft.executestatement(auth, select)
    numcols = length(columns)
    rows = strsplit(result, "\n")
    for (i in 3:length(rows[[1]])) {
    	row = strsplit(rows[[c(1,i)]], ",")
    	mdata = rbind(mdata, row[[1]])
   	}
   	output.frame = data.frame(mdata[2:length(mdata[,1]), 1])
   	for (i in 2:ncol(mdata)) {
   		output.frame = cbind(output.frame, mdata[2:length(mdata[,i]),i])
   	}
   	colnames(output.frame) = columns$names
    return (output.frame)
}

quote_value <- function(value, to_quote = FALSE, quote = "'") {
	 ret_value = ""
     if (to_quote) {
     	ret_value = paste(quote, paste(value, quote, sep=""), sep="")
     } else {
     	ret_value = value
     }
     return (ret_value)
}

converttostring <- function(arr, separator = ", ", column_types) {
	con_string = ""
	for (i in 1:(length(arr) - 1)) {
		value = quote_value(arr[i], column_types[i] != "number")
		con_string = paste(con_string, value)
	    con_string = paste(con_string, separator, sep="")
	}

    if (length(arr) >= 1) {
    	value = quote_value(arr[length(arr)], column_types[length(arr)] != "NUMBER")
    	con_string = paste(con_string, value)
    }
}

ft.exportdata <- function(auth, input_frame, table_name, create_table) {
	if (create_table) {
       create.table = "CREATE TABLE "
       create.table = paste(create.table, table_name)
       create.table = paste(create.table, "(")
       cnames = colnames(input_frame)
       for (columnname in cnames) {
         create.table = paste(create.table, columnname)
    	 create.table = paste(create.table, ":string", sep="")
    	   if (columnname != cnames[length(cnames)]){
    		  create.table = paste(create.table, ",", sep="")
           }
       }
      create.table = paste(create.table, ")")
      result = ft.executestatement(auth, create.table)
    }
    if (length(input_frame[,1]) > 0) {
    	tableid = ft.idfromtablename(auth, table_name)
	    columns = ft.describetablebyid(auth, tableid)
	    column_spec = ""
	    for (i in 1:length(columns$names)) {
		   column_spec = paste(column_spec, columns[i, 2])
		   if (i < length(columns$names)) {
			  column_spec = paste(column_spec, ",", sep="")
		   }
	    }
    	insert_prefix = "INSERT INTO "
    	insert_prefix = paste(insert_prefix, tableid)
    	insert_prefix = paste(insert_prefix, "(")
    	insert_prefix = paste(insert_prefix, column_spec)
    	insert_prefix = paste(insert_prefix, ") values (")
    	insert_suffix = ");"
    	insert_sql_big = ""
    	for (i in 1:length(input_frame[,1])) {
    		data = unlist(input_frame[i,])
    		values = converttostring(data, column_types  = columns$types)
    		insert_sql = paste(insert_prefix, values)
    		insert_sql = paste(insert_sql, insert_suffix) ;
    		insert_sql_big = paste(insert_sql_big, insert_sql)
    		if (i %% 500 == 0) {
    			ft.executestatement(auth, insert_sql_big)
    			insert_sql_big = ""
    		}
    	}
        ft.executestatement(auth, insert_sql_big)
    }
}

Using #Rstats for online data access

There are multiple packages in R to read data straight from online datasets.
These are as follows- Continue reading “Using #Rstats for online data access”