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What is SQL?

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SQL (pronounced ess-que-el) stands for Structured Query Language. SQL is used to communicate with a database. According to ANSI (American National Standards Institute), it is the standard language for relational database management systems. SQL statements are used to perform tasks such as update data on a database, or retrieve data from a database. Some common relational database management systems that use SQL are: Oracle, Sybase, Microsoft SQL Server, Access, Ingres, etc. Although most database systems use SQL, most of them also have their own additional proprietary extensions that are usually only used on their system. However, the standard SQL commands such as Select, Insert, Update, Delete, Create, and Drop can be used to accomplish almost everything that one needs to do with a database. This tutorial will provide you with the instruction on the basics of each of these commands as well as allow you to put them to practice using the SQL Interpreter.

Google Trends

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Google Trendsis a public web facility ofGoogle Inc., based onGoogle Search, that shows how often a particular search-term is entered relative to the total search-volume across various regions of the world, and in various languages. The horizontal axis of the main graph represents time (starting from 2004), and the vertical is how often a term is searched for relative to the total number of searches, globally. Below the main graph, popularity is broken down by countries, regions, cities and language. Note that what Google calls language, however, does not display the relative results of searches in different languages for the same term(s). It only displays the relative combined search volumes from all countries that share a particular language (see flowers vs fleurs). It is possible to refine the main graph by region and time period. On August 5, 2008, Google launchedGoogle Insights for Search, a more sophisticated and advanced service displaying search trends data. On September 27, 2012, Google merged Google Insights for Search into Google Trends.1

Google Trends also allows the user to compare the relative search volume of searches between two or more terms.

Originally, Google neglected updating Google Trends on a regular basis. In March 2007, internet bloggers noticed that Google had not added new data since November 2006, and Trends was updated within a week. Google did not update Trends from March until July 30, and only after it was blogged about, again.2Google now claims to be updating the information provided by Google Trends daily; Hot Trends is updated hourly.

On August 6, 2008, Google launched a free service called Insights for Search. Insights for Search is an extension of Google Trends and although the tool is meant for marketers, it can be utilized by any user. The tool allows for the tracking of various words and phrases that are typed into Googles search-box. The tracking device provided a more-indepth analysis of results. It also has the ability to categorize and organize the data, with special attention given to the breakdown of information by geographical areas.3In 2012, the Insights for Search has been merged into Google Trends with a new interface.

In 2009,Yossi Matiaset al. published research on the predictability of search trends.4In a series of highly influential articles in The New York Times, Seth Stephens-Davidowitz used Google Trends to measure a variety of behaviors. For example, in June 2012, he argued that search volume for the word nigger(s) could be used to measure racism in different parts of the United States. Correlating this measure with Obamas vote share, he calculated that Obama lost about 4 percentage points due to racial animus in the 2008 presidential election.5He also used Google data, along with other sources, to estimate the size of the gay population. This article noted that the most popular search beginning is my husband is is my husband gay?6In addition, he found that American parents were more likely to search is my son gifted? than is my daughter gifted? But they were more likely to search is my daughter overweight? than is my son overweight?7He also examined cultural differences in attitudes around pregnancy.8

Evidence is provided byJeremy Ginsberget al. that Google Trends data can be used to track influenza-like illness in a population.9Because the relative frequency of certain queries is highly correlated with the percentage of physician visits in which a patient presents with influenza-like symptoms, an estimate of weekly influenza activity can be reported. A more sophisticated model for inferring influenza rates from Google Trends, capable of overcoming the mistakes of its predecessors has been proposed by Lampos et al.10Inferences (influenza-like illness rates) from this model for England are presented on theFlu Detectorwebsite.

Furthermore, it was shown byTobias Preiset al. that there is a correlation between Google Trends data of company names and transaction volumes of the corresponding stocks on a weekly time scale.1112

In April 2012,Tobias PreisHelen Susannah MoatH. Eugene StanleyandSteven R. Bishopused Google Trends data to demonstrate that Internet users from countries with a higher per capita gross domestic product (GDP) are more likely to search for information about the future than information about the past. The findings, published in the journalScientific Reports, suggest there may be a link between online behaviour and real-world economic indicators.131415The authors of the study examined Google search queries made by Internet users in 45 different countries in 2010 and calculated the ratio of the volume of searches for the coming year (2011) to the volume of searches for the previous year (2009), which they call the future orientation index. They compared the future orientation index to the per capita GDP of each country and found a strong tendency for countries in which Google users enquire more about the future to exhibit a higher GDP. The results hint that there may potentially be a relationship between the economic success of a country and the information-seeking behaviour of its citizens online.

In April 2013,Tobias Preisand his colleaguesHelen Susannah MoatandH. Eugene Stanleyintroduced a method to identify online precursors for stock market moves, using trading strategies based on search volume data provided by Google Trends.16Their analysis ofGooglesearch volume for 98 terms of varying financial relevance, published inScientific Reports,17suggests that increases in search volume for financially relevant search terms tend to precede large losses in financial markets.1819202122232425

The analysis of Tobias Preis was later found to be misleading and the results are most likely to be overfitted.26The group of Damien Challet tested the same methodology with unrelated to financial markets search words, such as terms for diseases, car brands or computer games. They have found that all these classes provide equally good predictability of the financial markets as the original set. For example, the search terms like bone cancer, Shelby GT 500 (car brand), Moon Patrol (computer game) provide even better performance as those selected in original work.17

Google has incorporated quota limits for Trends searches. This limits the number of search attempts available per user/IP/device. Details of quota limits have not yet been provided, but it may depend on geographical location or browser privacy settings. It has been reported in some cases that this quota is reached really quickly if you are not logged in into your Google account before trying to access the trends service27

Google Hot Trends is an addition to Google Trends which displays the top 20 hot, i.e., fastest rising, searches (search-terms) of the past hour in various countries. This is for searches that have recently experienced a sudden surge in popularity.28For each of the search-terms, it provides a 24-hour search-volume graph as well as blog, news and web search results. Hot Trends has a history feature for those wishing to browse past hot searches. Hot Trends can be installed as aniGoogleGadget. Hot Trends is also available as an hourly.

Since 2008 there has been a sub-section of Google Trends which analyses traffic for websites, rather than traffic for search terms. This is a similar service to that provided byAlexa Internet. The Google Trends for Websites became unavailable after the September 27th, 2012 release of the new google trends product.29

An API to accompany the Google Trends service was announced byMarissa Mayer, then vice president of search-products and user experience at Google. This was announced in 2007, and so far has not been released.30

A few unofficial Google Trends API tools have been released, along with a wiki detailing them and simple access to Google Trends data. In addition, in May 2018, software developer Martin Spano released an extension of Google Trends calledKeywordsApp, which is online database of over 300 million top Google keywords.31

A group of researchers at Wellesley College examined data from Google Trends and analyzed how effective a tool it could be in predicting U.S. Congressional elections in 2008 and 2010. In highly contested races where data for both candidates were available, the data successfully predicted the outcome in 33.3% of cases in 2008 and 39% in 2010. The authors conclude that, compared to the traditional methods of election forecasting, incumbency and New York Times polls, and even in comparison with random chance, Google Trends did not prove to be a good predictor of either the 2008 or 2010 elections.32Another group has also explored possible implications for financial markets and suggested possible ways to combine insights from Google Trends with other concepts in technical analysis.33

Insights into what the world is searching for — the new Google Trends

Yossi Matias, Insights Search, The official Google Search blog, September 28, 2012.

Helft, Miguel (August 6, 2008).Googles New Tool Is Meant for Marketers.

On the predictability of Search Trends

Yossi Matias, Niv Efron, and Yair Shimshoni, Insights Search, Google Research blog, August 17, 2009.

Stephens-Davidowitz, Seth.How Racist Are We? Ask Google. The New York Times.

Stephens-Davidowitz, Seth.How Many American Men Are Gay?. The New York Times.

Stephens-Davidowitz, Seth.Tell Me, Google. Is My Son a Genius?. The New York Times.

Stephens-Davidowitz, Seth.What Do Pregnant Women Want. The New York Times.

Jeremy Ginsberg; Matthew H. Mohebbi; Rajan S. Patel; Lynnette Brammer; Mark S. Smolinski; Larry Brilliant (2009). Detecting influenza epidemics using search engine query data.

(7232): 10121014.Bibcode2009Natur.457.1012Gdoi10.1038/nature07634PMID19020500.

Lampos, Vasileios; Miller, Andrew C.; Crossan, Steve; Stefansen, Christian (3 Aug 2015).Advances in nowcasting influenza-like illness rates using search query logs.


Tobias Preis; Daniel Reith; H. Eugene Stanley (2010). Complex dynamics of our economic life on different scales: insights from search engine query data.

Philosophical Transactions of the Royal Society A

: 57075719.Bibcode2010RSPTA.368.5707Pdoi10.1098/rsta.2010.0284PMID21078644.

Catherine Mayer (November 15, 2010).Study: Are Google Searches Affecting the Stock Market?.

Tobias Preis, Helen Susannah Moat, H. Eugene Stanley and Steven R. Bishop (2012).Quantifying the Advantage of Looking Forward.

: 350.Bibcode2012NatSR…2E.350Pdoi10.1038/srep00350PMC

CS1 maint: Multiple names: authors list (link)

Paul Marks (April 5, 2012).Online searches for future linked to economic success.

Casey Johnston (April 6, 2012).Google Trends reveals clues about the mentality of richer nations.

Philip Ball(April 26, unting Google searches predicts market movements.

Tobias Preis; Helen Susannah Moat; H. Eugene Stanley (2013).Quantifying Trading Behavior in Financial Markets Using Google Trends.

: 1684.Bibcode2013NatSR…3E1684Pdoi10.1038/srep01684PMC

Nick Bilton (April 26, 2013).Google Search Terms Can Predict Stock Market, Study Finds.

Christopher Matthews (April 26, 2013).Trouble With Your Investment Portfolio? Google It!.

Philip Ball (April 26, 2013).Counting Google searches predicts market movements.

Big Data Researchers Turn to Google to Beat the Markets.

Hamish McRae (April 28, 2013).Hamish McRae: Need a valuable handle on investor sentiment? Google it.

Richard Waters (April 25, 2013).Google search proves to be new word in stock market prediction.

David Leinweber (April 26, 2013).Big Data Gets Bigger: Now Google Trends Can Predict The Market.

Jason Palmer (April 25, 2013).Google searches predict market moves.

Challet, Damien; Ayed, Ahmed Bel Hadj (2013-07-17). Predicting financial markets with Google Trends and not so random keywords.arXiv:

Insights into what the world is searching for — the new Google Trends

, Insights Search, The official Google Search blog, September 28, 2012.

Elinor Mills (December 4, 2007).Google Trends API coming soon

Cole, Karen.Programmer has outsmarted Google and collected a unique database.

On the Predictability of the U.S. Elections Through Search Volume Activity, at Journalists

Lim, Shawn, Stridsberg, Douglas (2014). Feeling the Markets Pulse with Google Trends.

International Federation of Technical Analysts Journal 2015 Edition

CS1 maint: Multiple names: authors list (link)

Google Hot Trends Webpage of top 20 search-terms, each linked to 24-hour graph & data.

List of mergers and acquisitions by Alphabet

Google: Behind the Screen (2006 documentary)

Computer-related introductions in 2006

CS1 maint: Multiple names: authors list

Articles needing additional references from March 2009

All articles needing additional references

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Select Tab name and columns to display in this Tab, then click on CREATE buttonData Feed – The location of the datafeed marketplace.Time Left – Domain Auction Time LeftTraffic – Traffic Estimation provided by Auction HouseFake – Google Suspicious Page Rank IndicatorYD – Domain listed in Yahoo DirectoryGD – Domain listed in Google DirectoryAge – Domain age derived from whoisGR – Number of Google search results for domain with extensionGRN – Number of Google search results for domain without extensionGIDX – Number of pages for the domain that are indexed with GoogleOVT – Number of overture search results for domain with extensionOVTN – Number of overture search results for domain without extensionMBL – Number of MajesticSEO Backlinks for this domain.MGOV – Number of MajesticSEO GOV Backlinks for this domain.MEDU – Number of MajesticSEO EDU Backlinks for this domain.MIC – Number of MajesticSEO Index Count for this domain.MIPS – Number of MajesticSEO Class C Ips for this domain.YBL – Number of Yahoo backlinks for domainGBL – Number of Google backlinks for domainABL – Number of Alexa backlinks for domainAVBL – Number of Altavista backlinks for domainEDU – Number of EDU backlinks for domainGOV – Number of GOV backlinks for domainWBR – Number of records for domainAPOP – Alexa Popularity Rank AnalyticALR – Alexa Popularity Reach AnalyticAFake – Alexa Suspicious Rank IndicatorAPV – Alexa Global Percent Page Views 3 MonthAPVU – Alexa Pageviews Per User 3 MonthREGC – Number that is registered in , , .ORG, , , ) extensionsQTR – Quantcast Traffic – Visits per MonthWTS – Number of Wordtracker searches for keyword-keyphraseGS – Number of Google searches for keyword-keyphraseGCPC – Google average cost per click for keyword-keyphrase adsGCLK – Google average monthly clicks for keyword-keyphrase adsGINC – Google average income for keyword-keyphrase adsGADV – Google number of advertisers for keyword-keyphrase ads

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Boobs Sizing Up the Searches

In this edition of Pornhub Insights, well be getting abreast of a topic thats near and dear to the heart of many Pornhub fans Boobs! We paired up with our friends atMashableto find out what the most popular breast related searches are, as well as what demographics, countries and states are most interested in searching for them. To shake things up, well be breaking our stats into searches for big breasts versus small breasts, and also fake breasts versus the real thing.

The number one breast related search on Pornhub is big tits, followed by big boobs and huge tits. It seems that authenticity is important to Pornhubs visitors, as big natural boobs rank fourth overall in fact any searches related to fake boobs dont make the top 25 of breast related terms.

Overall, daily breast related searches number in the millions, making up around 1.5% of all searches entered on Pornhub each day. The following chart shows how the popularity of the four major breast types stack up next to each other. Large breast searches are ten times the size of small, and natural is around five times more popular than fake.

The following word-clouds illustrate proportionately how popular various search terms are within either the large or the small breast genres. Some terms combined with large breast searches include massive, redhead, asian, teacher and pov (point of view). Small breast related searches are often combined with terms like puffy nipples, mature, saggy, and tiny.

The following word-clouds illustrate proportionately how popular various search terms are within either the fake or natural breast genres. Some terms combined with fake breast searches include perfect, impossible, monster, massive and giant. Natural breast related searches are often combined with terms like bouncing, perfect, saggy, amateur and skinny.

Over time, weve seen the popularity of both large and small breast searches fluctuate. The following chart illustrates the growth of each type of search on their own scales (not in comparison to each other) from January 2013 to July of 2017.

Both breast types saw a surge in popularity in the spring of 2014, but small breasts have shown significant growth over the past 12 months, while during the same period large breasts lost some of their support.

The following chart illustrates the changes in search popularity of both fake and natural breasts on their own scales (not in comparison to each other) from January 2013 to July of 2017.

Fake breast searches were quite popular in early 2013, but began to sag near the beginning of 2014 before inflating back up to an above average level between April 2014 to April 2015. Since then, fake breasts seem to have lost some of their support. Natural breasts experienced their biggest growth period from January 2015 to April of 2016, but have decreased in popularity again over the last year.

When it comes to who likes boobs the breast, its men who are 32% more likely to search for breast related terms when compared towomen. Pornhub visitors between the ages of 18 to 24 are 19% less likely to search for breasts when compared to all other age groups, but visitors aged 55 to 64 are 17% more likely to search.

Men are once again 64% more likely to search for large breasts compared to women, and 183% more likely to search for small breast related terms.Millennialsbetween the ages of 18 to 34 are far less likely to search for both big or small breasts compared to most age groups over the age of 35.

Proportionately, men are 130% more likely to search for fake breasts compared towomen, and 78% more likely to search for natural breasts. Fake breasts are most popular with Pornhub visitors between the ages of 25 to 44, but the popularity of those newfangled boob-balloons is significantly lower with visitors over the age of 55. Conversely, natural breasts are far less popular with millennials between the ages of 18 and 34, while the real thing is most appreciated by visitors between the ages of 45 to 64.

Now lets take a look at how breasts stack up across theUnited States of America. Proportionately, the states most interested in search for breasts are Wisconsin, Minnesota, Oregon,Utahand Washington. Visitors from Mississippi, Hawaii, Delaware, Louisiana and theDistrict of Colombiahave the lowest proportion of searches.

Searches for large breasts are most popular in California, Wisconsin, Minnesota and (everything is bigger in) Texas. The states least interested in searching for large breasts are Mississippi, Hawaii, Delaware and Louisiana. Interest in small breasts is not necessarily an indication that the same people like large breasts. In fact, we see many of the same states likely to search for both types. Wisconsin and Minnesota are again quite interested in seeking small breasts, while Pornhubs visitors from Mississippi, Hawaii and Delaware are equally less interested in small as large.

The states that are proportionately the most likely to search for fake breasts are Utah, Idaho, Oregon, Arizona and California. They are least popular in Delaware, Mississippi and Alaska. Natural breasts are more popular in Wisconsin, Oregon, Minnesota and Washington, but less popular in Hawaii, Mississippi and Delaware.

Finally, lets take a look at the countries which are more or less interested in breasts, and what types they prefer. The country that proportionately searches the most often for breasts is Nigeria, followed byFinland,Canada,United Kingdomand the United States. Breast related searches are least common in Peru, Brazil,Argentina, Chile, Mexico, Algeria andRussia.

Large breasts are again biggest in Nigeria, along with Finland, Indonesia and Canada. The countries least interested in big breasts are Egypt, Colombia and Argentina. Small breasts are also quite popular with visitors from Finland and Canada, but Columbia is the country least interested in searching for them.

With the exception of Canada and Australia, the top ten countries searching for fake breasts are all located in Europe including Denmark, Sweden, Finland, Norway and Austria. Many of these countries also have a significant number of visitors searching for natural breasts.

We hope you enjoyed this edition of Pornhub Insights. Stay tuned for more great Insights to come, and as always let us know your thoughts in the comments below!

Pornhub Insights is research and analysis directly from the Pornhub team. Weve compiled data from billions of hits, all to explore the intricacies of online porn is the worlds biggest porn site. Follow Insights for stats, events, and Pornhub related announcements.

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