Sql Quotes

The moral of the story is that a NoSQL system may find itself accidentally reinventing SQL, albeit in disguise.

Master Oracle Advanced PL/SQL concepts with the book

But you’re more at home with SQL than socialization: Innuendo wasn’t a language they taught in CS lab.

In the case of querymongo.com, RJMetrics built a tool that translates SQL queries to MongoDB syntax (two database technologies). This

This new science of performance argues that you get better at a skill as you develop more myelin around the relevant neurons, allowing the corresponding circuit to fire more effortlessly and effectively. To be great at something is to be well myelinated. This understanding is important because it provides a neurological foundation for why deliberate practice works. By focusing intensely on a specific skill, you’re forcing the specific relevant circuit to fire, again and again, in isolation. This repetitive use of a specific circuit triggers cells called oligodendrocytes to begin wrapping layers of myelin around the neurons in the circuits—effectively cementing the skill. The reason, therefore, why it’s important to focus intensely on the task at hand while avoiding distraction is because this is the only way to isolate the relevant neural circuit enough to trigger useful myelination. By contrast, if you’re trying to learn a complex new skill (say, SQL database management) in a state of low concentration (perhaps you also have your Facebook feed open), you’re firing too many circuits simultaneously and haphazardly to isolate the group of neurons you actually want to strengthen. In

Different databases are designed to solve different problems. Using a single database engine for all of the requirements usually leads to non- performant solutions; storing transactional data, caching session information, traversing graph of customers and the products their friends bought are essentially different problems.

Unlike in most programming languages, SQL treats null as a special value, different from zero, false, or an empty string.

The presence of a column named id in every table is so common that this has become synonymous with a primary key. Programmers learning SQL get the false idea that a primary key always means a column defined in this manner.

using SQL to search by keywords, while also making the solution both fast and accurate, is deceptively difficult.

SQL is correctly pronounced “ess-cue-ell,” not “see-quell.

When you execute a program that retrieves a small subset of rows from a large table, it can be time-consuming for PROC SQL to read the rows sequentially. In some situations, using an index on a table allows PROC SQL to access a subset of rows more efficiently. An index stores unique values for a specified column or columns in ascending value order, and includes information about the location of those values in the table. That is, an index is composed of value/identifier pairs that enable you to access a row directly, by value. For example, suppose you have created an index on your table that is based

comments:\n".$feedback."\n"; $fromaddress 

One scenario could be where you have a source

Complex applications combine different types of problems, so picking the right language for each job may be more productive than trying to fit all aspects into a single language.

This had all the earmarks of an SQL-injection attack, and he had a favorite one. In the logon and password boxes he entered: ‘or 1=1--

Dimensional models implemented in relational database management systems are referred to as star schemas because of their resemblance to a star-like structure. Dimensional models implemented in multidimensional database environments are referred to as online analytical processing (OLAP) cubes, as illustrated in Figure 1.1. Figure 1.1 Star schema versus OLAP cube. If your DW/BI environment includes either star schemas or OLAP cubes, it leverages dimensional concepts. Both stars and cubes have a common logical design with recognizable dimensions; however, the physical implementation differs. When data is loaded into an OLAP cube, it is stored and indexed using formats and techniques that are designed for dimensional data. Performance aggregations or precalculated summary tables are often created and managed by the OLAP cube engine. Consequently, cubes deliver superior query performance because of the precalculations, indexing strategies, and other optimizations. Business users can drill down or up by adding or removing attributes from their analyses with excellent performance without issuing new queries. OLAP cubes also provide more analytically robust functions that exceed those available with SQL. The downside is that you pay a load performance price for these capabilities, especially with large data sets.

The constraints of a toolset help to define patterns for solving problems. In the case of MongoDB, one of those constraints is the lack of atomic multidocument update operations. The patterns we use in MongoDB to mitigate the lack of atomic multidocument update operations include document embedding and complex updates for basic operations, with optimistic update with compensation available for when we really need a two-phase commit protocol. When designing your application to use MongoDB, more than in relational databases, you must keep in mind which updates you need to be atomic and design your schema appropriately.

larger

The fewer documents in RAM, the more likely the server is to page fault to retrieve documents, and ultimately page faults lead to random disk I/O.

One final factor that weighs in favor of using document references is the case of many-to-many or M:N relationships.

MongoDB was designed from the ground up to be easy to scale to multiple distributed servers. Two of the biggest problems in distributed database design are distributed join operations and distributed transactions.

In a RDBMS, since all the column names and types are defined at the table level, this information does not need to be replicated in each row. MongoDB, by contrast, doesn’t know, at the collection level, what fields are present in each document, nor does it know their types, so this information must be stored on a per-document basis.

By “punting” on these problems and not supporting joins or multidocument transactions at all, MongoDB has been able to implement an automatic sharding solution with much better scaling and performance characteristics than you’d normally be stuck with if you had to take relational joins and transactions into account.

USE AdventureWorks GO sp_helpstats ‘Person.Contact’; For a complete lesson on Statistics see Chapters 12 of SQL Architecture Basics Joes 2 Pros Volume 3 ISBN: 1451579462. Points to Ponder from SQL Queries Joes 2 Pros Volume 2 ISBN: 1-4392-5318-8 (Joes2Pros.com)

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To make sure your strings go from PHP to MySQL as UTF-8, make sure your database and tables are all set to the utf8mb4 character set and collation, and that you use the utf8mb4 character set in the PDO connection string.

Leiderman, his lawyer, scrambled to get Royal a lesser sentence, perhaps some kind of house arrest so he could continue working and going to school. He was frustrated with the law on this matter. “We’re over-criminalizing childish mischief,” he said. “A twelve-year-old with moderate knowledge of computers could have signed up for a VPN and used this SQL tool Havij and, with the instructions he had, done this attack. [Royal] has lived an exemplary life, and gets what he did. We don’t need to be locking people like that up.

Another method for scaling the database layer is to run a MySQL Cluster

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One of the more popular methods for scaling the database layer is to run a Galera Cluster for MySQL

Management OS should be nothing but a Management OS for Hyper-V. Don’t make it a domain controller, don’t install SQL Server, don’t turn it into a Remote Desktop Services session host; Microsoft’s support services won’t like it. Instead, install those applications in virtual machines that are running on the host.

SQL Server itself and SQL Server Management Studio (SMSS). 

One class of software, broadly known as analytical databases, dispenses with the relational model. Using innovations in on-disk storage and the use of distributed memory, analytical databases combine the flexibility of SQL with the speed of traditional OLAP systems.

With Dremel, engineers could formulate queries using an SQL-like syntax, speeding up the process of iterative analysis without dealing with the overhead of defining raw MapReduce jobs.

Web Application Development In this modern world of computer technology all people are using internet. In particular, to take advantage of this scenario the web provides a way for marketers to get to know the people visiting their sites and start communicating with them. One way of doing this is asking web visitors to subscribe to newsletters, to submit an application form when requesting information on products or provide details to customize their browsing experience when next visiting a particular website. In computing, a web application is a client–server software application in which the client runs in a web browser. HTML5 introduced explicit language support for making applications that are loaded as web pages, but can store data locally and continue to function while offline. Web Applications are dynamic web sites combined with server side programming which provide functionalities such as interacting with users, connecting to back-end databases, and generating results to browsers. Examples of Web Applications are Online Banking, Social Networking, Online Reservations, eCommerce / Shopping Cart Applications, Interactive Games, Online Training, Online Polls, Blogs, Online Forums, Content Management Systems, etc.. Applications are usually broken into logical chunks called “tiers”, where every tier is assigned a role. Traditional applications consist only of 1 tier, which resides on the client machine, but web applications lend themselves to an n-tiered approach by nature. Though many variations are possible, the most common structure is the three-tiered application. In its most common form, the three tiers are called presentation, application and storage, in this order. A web browser is the first tier (presentation), an engine using some dynamic Web content technology (such as ASP, CGI, ColdFusion, Dart, JSP/Java, Node.js, PHP, Python or Ruby on Rails) is the middle tier (application logic), and a database is the third tier (storage).The web browser sends requests to the middle tier, which services them by making queries and updates against the database and generates a user interface. Client Side Scripting / Coding – Client Side Scripting is the type of code that is executed or interpreted by browsers. Client Side Scripting is generally viewable by any visitor to a site (from the view menu click on “View Source” to view the source code). Below are some common Client Side Scripting technologies: HTML (HyperTextMarkup Language) CSS (Cascading Style Sheets) JavaScript Ajax (Asynchronous JavaScript and XML) jQuery (JavaScript Framework Library – commonly used in Ajax development) MooTools (JavaScript Framework Library – commonly used in Ajax development) Dojo Toolkit (JavaScript Framework Library – commonly used in Ajax development) Server Side Scripting / Coding – Server Side Scripting is the type of code that is executed or interpreted by the web server. Server Side Scripting is not viewable or accessible by any visitor or general public. Below are the common Server Side Scripting technologies: PHP (very common Server Side Scripting language – Linux / Unix based Open Source – free redistribution, usually combines with MySQL database) Zend Framework (PHP’s Object Oriented Web Application Framework) ASP (Microsoft Web Server (IIS) Scripting language) ASP.NET (Microsoft’s Web Application Framework – successor of ASP) ColdFusion (Adobe’s Web Application Framework) Ruby on Rails (Ruby programming’s Web Application Framework – free redistribution) Perl (general purpose high-level programming language and Server Side Scripting Language – free redistribution – lost its popularity to PHP) Python (general purpose high-level programming language and Server Side Scripting language – free redistribution). We also provide Training in various Computer Languages. TRIRID provide quality Web Application Development Services. Call us @ 8980010210

...SQL is very far from being the “perfect” relational language—it suffers from numerous sins of both omission and commission. ...the overriding issue is simply that SQL fails in all too many ways to support the relational model properly. As a consequence, it is not at all clear that today's SQL products really deserve to be called “relational” at all! Indeed, as far as this writer is aware, there is no product on the market today that supports the relational model in its entirety. This is not to say that some parts of the model are unimportant; on the contrary, every detail of the model is important, and important, moreover, for genuinely practical reasons. Indeed, the point cannot be stressed too strongly that the purpose of relational theory is not just “theory for its own sake”; rather, the purpose is to provide a base on which to build systems that are 100 percent practical. But the sad fact is that the vendors have not yet really stepped up to the challenge of implementing the theory in its entirety. As a consequence, the “relational” products of today regrettably all fail, in one way or another, to deliver on the full promise of relational technology.

I want to migrate us to MySQL and open-source databases wherever we can, because I’m tired of sending millions of dollars each year to an abusive vendor.

With explicitly delineated levels of service, the infrastructure providers can effectively externalize the difference in the cost it takes to provide service at a given level to clients. Exposing cost in this way motivates the clients to choose the level of service with the lowest cost that still meets their needs. For example, Google + can decide to put data critical to enforcing user privacy in a high-availability, globally consistent datastore (e.g., a globally replicated SQL-like system like Spanner [Cor12]), while putting optional data (data that isn’t critical, but that enhances the user experience) in a cheaper, less reliable, less fresh, and eventually consistent datastore (e.g., a NoSQL store with best-effort replication like Bigtable).

SQL (Structured Query Languaje) no es más que un conjunto de palabras y una serie de reglas diseñadas única y exclusivamente para comunicarnos con una base de datos.

Una base de datos no es más que un software, esto es, un programa como puede ser un sistema operativo o un antivirus, cuyo principal objetivo es almacenar información.

Facebook decided to invest in Hive, a SQL-like language that would be more optimal for Hadoop, and a unique tooling layer called HiPal that would be the primary GUI for Hive. HiPal allowed any user to see what others in the company were accessing. This unique form of transparency allowed a new user to get up to speed quickly by studying what other people on the team were requesting and then building on it.

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MySQL and PHP for Web Development (you can’t hear it right now, but every time I read those words, angels in heaven sing to me.) Now

Oracle 12c Enterprise or Standard Edition – building on Oracle’s unique ability to deliver Grid Computing, 12c gives Oracle customers the agility to respond faster to changing business conditions, gain competitive advantage through technology innovation, and reduce costs.

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Organizations seeking to commercialize open source software realized this, of course, and deliberately incorporated it as part of their market approach. In a 2013 piece on Pando Daily, venture capitalist Danny Rimer quotes then-MySQL CEO Mårten Mickos as saying, “The relational database market is a $9 billion a year market. I want to shrink it to $3 billion and take a third of the market.” While MySQL may not have succeeded in shrinking the market to three billion, it is interesting to note that growing usage of MySQL was concurrent with a declining ability of Oracle to sell new licenses. Which may explain both why Sun valued MySQL at one third of a $3 billion dollar market and why Oracle later acquired Sun and MySQL. The downward price pressure imposed by open source alternatives have become sufficiently visible, in fact, as to begin raising alarm bells among financial analysts. The legacy providers of data management systems have all fallen on hard times over the last year or two, and while many are quick to dismiss legacy vendor revenue shortfalls to macroeconomic issues, we argue that these macroeconomic issues are actually accelerating a technology transition from legacy products to alternative data management systems like Hadoop and NoSQL that typically sell for dimes on the dollar. We believe these macro issues are real, and rather than just causing delays in big deals for the legacy vendors, enterprises are struggling to control costs and are increasingly looking at lower cost solutions as alternatives to traditional products. — Peter Goldmacher Cowen and Company

As such, the company’s value from a technology perspective isn’t software, strictly speaking, but rather outsourced effort. Any business can download and run software like MySQL or PostgreSQL at no cost. But hosting it, keeping it up and running, backing up the databases, and exposing them safely to other applications requires expertise and effort. For many customers, and AWS customers in particular, then, the value isn’t in the software itself — because that is available at no cost — but the saved expertise and effort of consuming the infrastructure software as a service. Amazon, in other words, is making money with software, rather than from software.

At MySQL, there were 400 employees in 40 countries, with 95% of the development staff working from home. The challenges this model presented, from time zone differences to communication technologies to project coordination to legal and commercial logistics, were immense. But it offset these costs with hard savings on real estate, salaries, and improvements in productivity. Most importantly, allowing workers to work remotely is like selling from the Internet: you’re no longer limited by your local geography.

print "Hello World!" Write this code in a text file and save it as main.py. Execute the code by writing main.py on the python command prompt to get the desired result.

The best teachers do not simply spout information at their students and hope for the best. The best teachers are those who set expectations responsibly and ensure that students adopt a resilient, “can-do” frame of mind.

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The SQL statement is passed as a simple string. If user-controllable input is part of the string parameter, the application is probably vulnerable to SQL injection.

MySQL 8 currently supports horizontal partitioning.

A good architecture makes it unnecessary to decide on Rails, or Spring, or Hibernate, or Tomcat, or MySQL, until much later in the project. A good architecture makes it easy to change your mind about those decisions, too. A good architecture emphasizes the use cases and decouples them from peripheral concerns

As psychologists, Ericsson and the other researchers in his field are not interested in why deliberate practice works; they’re just identifying it as an effective behavior. In the intervening decades since Ericsson’s first major papers on the topic, however, neuroscientists have been exploring the physical mechanisms that drive people’s improvements on hard tasks. As the journalist Daniel Coyle surveys in his 2009 book, The Talent Code, these scientists increasingly believe the answer includes myelin—a layer of fatty tissue that grows around neurons, acting like an insulator that allows the cells to fire faster and cleaner. To understand the role of myelin in improvement, keep in mind that skills, be they intellectual or physical, eventually reduce down to brain circuits. This new science of performance argues that you get better at a skill as you develop more myelin around the relevant neurons, allowing the corresponding circuit to fire more effortlessly and effectively. To be great at something is to be well myelinated. This understanding is important because it provides a neurological foundation for why deliberate practice works. By focusing intensely on a specific skill, you’re forcing the specific relevant circuit to fire, again and again, in isolation. This repetitive use of a specific circuit triggers cells called oligodendrocytes to begin wrapping layers of myelin around the neurons in the circuits—effectively cementing the skill. The reason, therefore, why it’s important to focus intensely on the task at hand while avoiding distraction is because this is the only way to isolate the relevant neural circuit enough to trigger useful myelination. By contrast, if you’re trying to learn a complex new skill (say, SQL database management) in a state of low concentration (perhaps you also have your Facebook feed open), you’re firing too many circuits simultaneously and haphazardly to isolate the group of neurons you actually want to strengthen.

row context iterates; it does not filter.

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or custom

Some are proprietary, meaning they are owned by a company and cost money to use, and others are open source, meaning they are free for anyone to use. Table 1-1 details the differences between the RDBMSs.

Applications treating data as code is the root cause of almost every major class of vulnerability. Cross-site scripting happens when applications treat data as HTML or script. SQL injection happens when applications treat data as SQL. Buffer overflows happen when applications treat data as assembly code.

I've learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.” - Maya Angelou

Unfortunately, the SQL standard’s definition of isolation levels is flawed—it is ambiguous, imprecise, and not as implementation-independent as a standard should be [28]. Even though several databases implement repeatable read, there are big differences in the guarantees they actually provide, despite being ostensibly standardized [23]. There has been a formal definition of repeatable read in the research literature [29, 30], but most implementations don’t satisfy that formal definition. And to top it off, IBM DB2 uses “repeatable read” to refer to serializability [8]. As a result, nobody really knows what repeatable read means.

DBAs work exactly in the middle of sofware and hardware, between developers and operators and between applications and infrastructure. This position provides DBAs with all sorts of challenges, from a badly written SQL statement from developers to storage bottlenecks, from network latency problem to metadata definition, and from coding database procedures to defining hardware requirements for a new database.

The way xp_ cmdshell works is very simple: It takes a single string argument and then executes that as a command-line call. For example, the call would perform a directory listing of the server’s C drive. Again, at this point the damage is limited only by the attacker’s imagination, and exploiting this through SQL injection is absolutely trivial: If you’re running SQL Server, we strongly recommend disabling or removing the xp_cmdshell stored procedure. You can disable it through use of the sp_configure stored procedure, like so:

personal conversation last year, “SQL is the new HTML.” Database management is a core competency of Web 2.0 companies, so much so that we have sometimes referred to these applications as "infoware" rather than merely software. This fact leads to a key question: Who owns the data? In the internet era, one can already see a number of cases where control over the database has led to market control and outsized financial returns. The

By contrast, if you’re trying to learn a complex new skill (say, SQL database management) in a state of low concentration (perhaps you also have your Facebook feed open), you’re firing too many circuits simultaneously and haphazardly to isolate the group of neurons you actually want to strengthen.

The fact that SQL is more limited in functionality gives the database much more room for automatic optimizations.

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The filter context filters; the row context iterates.

Historically, data started out being represented as one big tree (the hierarchical model), but that wasn’t good for representing many-to-many relationships, so the relational model was invented to solve that problem. More recently, developers found that some applications don’t fit well in the relational model either. New nonrelational “NoSQL” datastores have diverged in two main directions: Document databases target use cases where data comes in self-contained documents and relationships between one document and another are rare. Graph databases go in the opposite direction, targeting use cases where anything is potentially related to everything.

Martin Fowler NoSQL Distilled: "In general, with remote communication you want to reduce the number of round trips involved in the interaction, so it’s useful to be able to put a rich structure of information into a single request or response." Patterns of Enterprise Application Architecture" "Due to the latency costs of remote calls, it's better to err on the side of sending too much data than have to make multiple calls.

Stored procedures can offer huge performance advantages for huge architectural costs. You may avoid streaming thousands of rows to a client application, but you have also bound your application code to this database. The decision to use stored procedures should not be arrived at lightly.

When expressing a regular character literal, you simply use single quotes: ‘This is a regular character string literal’. When expressing a Unicode character literal, you need to specify the character N (for National) as a prefix: N’This is a Unicode character string literal’.

Running multiple services on a single node is sometimes referred to as pancaking. 

You can scale without increasing availability or uptime. 

In many cases it makes sense to scale your web servers horizontally while you scale your database servers vertically. 

Example output:     Challenge Question 25: Top Territories Difficulty: Intermediate

Also, _netdev signals that networking needs to be started before the file system mount is even attempted.

Features of Cassandra In order to keep this chapter short, the following bullet list covers the great features provided by Cassandra: Written in Java and hence providing native Java support Blend of Google BigTable and Amazon Dynamo Flexible schemaless column-family data model Support for structured and unstructured data Decentralized, distributed peer-to-peer architecture Multi-data center and rack-aware data replication Location transparent Cloud enabled Fault-tolerant with no single point of failure An automatic and transparent failover Elastic, massively, and linearly scalable Online node addition or removal High Performance Built-in data compression Built-in caching layer Write-optimized Tunable consistency providing choices from very strong consistency to different levels of eventual consistency Provision of Cassandra Query Language (CQL), a SQL-like language imitating INSERT, UPDATE, DELETE, SELECT syntax of SQL Open source and community-driven

transporting data and deploying

When the query was finished getting results, we ended

The sqlalchemy module is to SQL geeks what requests is to web geeks: indispensable. The

MongoDB is sometimes referred to as a “schemaless” database, meaning that it does not enforce a particular structure on documents in a collection. It is perfectly legal (though of questionable utility) to store every object in your application in the same collection, regardless of its structure. In

Index design is also a largely iterative process, based on the SQL generated by application designers. However, it is possible to make a sensible start by building indexes that enforce primary key constraints and indexes on known access patterns, such as a person's name. As the application evolves and testing is performed on realistic sizes of data, certain queries will need performance improvements for which building a better index is a good solution.

As prevalent as disks once were, they are now a dying breed. Soon they will have gone the way of tape drives, floppy drives, and CDs. They are being replaced by RAM. Ask yourself this question: When all the disks are gone, and all your data is stored in RAM, how will you organize that data? Will you organize it into tables and access it with SQL? Will you organize it into files and access it through a directory? Of course not. You’ll organize it into linked lists, trees, hash tables, stacks, queues, or any of the other myriad data structures, and you’ll access it using pointers or references—because that’s what programmers do.

Bottled Water implements CDC for PostgreSQL using an API that decodes the write-ahead log [28], Maxwell and Debezium do something similar for MySQL by parsing the binlog [29, 30, 31], Mongoriver reads the MongoDB oplog [32, 33],

NoSQL databases emerged from unmet needs.

SELECT constraint_name, constraint_type, search_condition FROM user_constraints WHERE  table_name = 'AIRCRAFT_TYPES

By at least the summer of 2016, GRU officers sought access to state and local computer networks by exploiting known software vulnerabilities on websites of state and local governmental entities. GRU officers, for example, targeted state and local databases of registered voters using a technique known as "SQL injection," by which malicious code was sent to the state or local website in order to run commands (such as exfiltrating the database contents).188 In one instance in approximately June 2016, the GRU compromised the computer network of the Illinois State Board of Elections by exploiting a vulnerability in the SBOE's website. The GRU then gained access to a database containing information on millions of registered Illinois voters,189 and extracted data related to thousands of U.S. voters before the malicious activity was identified.190

Victims included U.S. state and local entities, such as state boards of elections (SBOEs), secretaries of state, and county governments, as well as individuals who worked for those entities.186 The GRU also targeted private technology firms responsible for manufacturing and administering election-related software and hardware, such as voter registration software and electronic polling stations.187 The GRU continued to target these victims through the elections in November 2016. While the investigation identified evidence that the GRU targeted these individuals and entities, the Office did not investigate further. The Office did not, for instance, obtain or examine servers or other relevant items belonging to these victims. The Office understands that the FBI, the U.S. Department of Homeland Security, and the states have separately investigated that activity. By at least the summer of 2016, GRU officers sought access to state and local computer networks by exploiting known software vulnerabilities on websites of state and local governmental entities. GRU officers, for example, targeted state and local databases of registered voters using a technique known as "SQL injection," by which malicious code was sent to the state or local website in order to run commands (such as exfiltrating the database contents).188 In one instance in approximately June 2016, the GRU compromised the computer network of the Illinois State Board of Elections by exploiting a vulnerability in the SBOE's website. The GRU then gained access to a database containing information on millions of registered Illinois voters,189 and extracted data related to thousands of U.S. voters before the malicious activity was identified.190 GRU officers [REDACTED: Investigative Technique] scanned state and local websites for vulnerabilities. For example, over a two-day period in July 2016, GRU officers [REDACTED: Investigative Technique] for vulnerabilities on websites of more than two dozen states.

Databases of this type are interrogated in a language called SQL. You send them commands like the one shown here to interact with their stored information. Understanding how to manipulate these databases is subtle. The example command, for example, creates a “view”: a virtual database table that pulls together data from multiple existing tables, and that can then be addressed by the SQL commands like a standard table. When to create views and how to do so well is a tricky question, one of many that you must understand and master to tease reasonable results out of real-world databases.