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The History of SQL: From Inception to Modern Database Systems SQL, or Structured Query Language, is the language that powers most of the world’s relational databases, enabling users to interact with data in a structured and accessible way. From its early theoretical underpinnings to its role in modern enterprise and cloud databases, SQL has a rich and evolving history. Let’s explore the story of SQL’s development, its transformations over the years, and its enduring relevance in the age of Big Data. 1. Early Foundations: The Birth of the Relational Model (1969–1970s) The history of SQL is rooted in the development of the relational model by Edgar F. Codd, an IBM researcher, in 1969. Codd's groundbreaking paper titled "A Relational Model of Data for Large Shared Data Banks" published in 1970 proposed a new way to organize and manipulate data. This model suggested that data could be stored in a table-like structure with rows and columns, making it easier to retrieve, modify, and manage information. Codd's ideas laid the theoretical foundation for relational databases, which would later become mainstream in the database world. The relational model’s promise of simplicity and consistency was revolutionary, as existing database models at the time—such as the hierarchical and network models—were complex and difficult to maintain. Key Components of Codd's Relational Model - Data Independence: Codd emphasized that the storage of data should be separate from the logical structure, allowing changes to the structure without impacting data access. - Structured Data Retrieval: The relational model introduced the concept of querying data through a declarative language, rather than navigating through complex data structures. 2. SQL's Early Development: SEQUEL at IBM (1974–1979) In 1974, two IBM researchers, Donald D. Chamberlin and Raymond F. Boyce, sought to implement Codd’s relational ideas practically. They developed a language called SEQUEL (Structured English Query Language) to interact with IBM’s System R, one of the first experimental relational database systems. SEQUEL allowed users to access and manipulate data in tables using an English-like syntax, making it accessible to non-technical users. However, due to trademark issues, SEQUEL was renamed to SQL (Structured Query Language). The language quickly gained traction due to its straightforward syntax and power in data management, establishing itself as the standard for relational databases. System R: The First SQL Implementation System R, developed at IBM’s San Jose Research Laboratory in the late 1970s, was the first implementation of SQL. The primary goal of System R was to test Codd’s relational model and prove that it could support robust database systems. The success of System R demonstrated SQL’s effectiveness in managing relational data, encouraging IBM to pursue further development. 3. The Rise of SQL as an Industry Standard (1980s) By the early 1980s, SQL was gaining industry recognition. In 1981, IBM released its SQL/DS product for mainframes, followed by DB2 in 1983, which brought SQL-based relational databases to the enterprise level. Meanwhile, other companies, including Oracle (then called Relational Software Inc.), recognized the commercial potential of SQL. Oracle released its first SQL-based relational database product, Oracle V2, in 1979, which ran on the then-novel operating system, VAX/VMS. This product was a turning point, as it made relational databases more widely available to businesses outside of IBM's ecosystem. ANSI and ISO Standardization (1986–1989) To promote interoperability across database systems, SQL underwent standardization in the mid-1980s. The American National Standards Institute (ANSI) adopted SQL as a standard in 1986, followed by the International Organization for Standardization (ISO) in 1987. This standardization of SQL led to wider adoption and compatibility between different database systems, paving the way for SQL to become the lingua franca of database management. 4. SQL’s Evolution in the Client-Server Era (1990s) As client-server computing became popular in the 1990s, relational databases and SQL adapted to new environments. SQL's role expanded beyond mainframes to include PCs and client-server architecture, making data more accessible to end-users. During this period, SQL underwent various improvements, driven largely by the SQL-92 standard, which introduced new features such as: - New Data Types: SQL-92 expanded the range of data types available. - Enhanced Querying Abilities: Subqueries, joins, and other powerful querying capabilities were added. - Transaction Control: SQL-92 standardized transaction controls, enhancing database reliability. With these advancements, SQL-based databases became the backbone of enterprise applications across industries, from finance to telecommunications. Companies like Microsoft with SQL Server and Oracle continued to innovate, providing robust database solutions for businesses worldwide. 5. SQL and the Internet Boom (Late 1990s–2000s) The advent of the internet in the late 1990s brought a surge in data generation. Websites needed dynamic, data-driven content, leading to a rapid adoption of SQL-based databases in web applications. MySQL and PostgreSQL, two open-source relational database management systems (RDBMS), became popular during this era due to their scalability and low cost, particularly among startups and web developers. MySQL, first released in 1995, gained traction as a part of the LAMP stack (Linux, Apache, MySQL, PHP/Python/Perl), which was widely used for web development. PostgreSQL, known for its support of advanced SQL features and extensibility, also found a strong following. These open-source options made SQL-based databases accessible to a broader audience, accelerating the growth of SQL. SQL Standardization in the 2000s The SQL-1999 and SQL:2003 standards introduced new features to support object-relational databases and XML data. These additions allowed SQL to handle more complex data types, further enhancing its versatility. 6. SQL in the Age of Big Data (2010s–Present) In the 2010s, the Big Data movement challenged traditional SQL-based systems. With the massive volume and variety of data generated by the internet, social media, and IoT devices, companies began adopting NoSQL databases like MongoDB and Cassandra, which were designed to handle unstructured data at scale. However, SQL’s ease of use and powerful querying capabilities kept it relevant, and soon, SQL-on-Hadoop solutions like Hive and Impala emerged to allow SQL querying on large, distributed datasets. The 2010s also saw the growth of cloud computing, which brought about cloud-native databases like Amazon’s Amazon RDS, Google’s BigQuery, and Microsoft’s Azure SQL Database. These services made it easy to deploy and manage SQL databases in the cloud, offering scalability and reliability for companies of all sizes. 7. Modern SQL Innovations (2020s and Beyond) Today, SQL continues to evolve, especially in cloud and hybrid environments. Modern SQL databases leverage distributed computing, in-memory processing, and machine learning capabilities to meet the demands of data-intensive applications. SQL databases now support: - JSON and Semi-Structured Data: With extensions for handling JSON, SQL can now process semi-structured data without sacrificing its structured nature. - Machine Learning Integrations: Many SQL-based systems now incorporate machine learning functions directly into the database, enabling advanced analytics. - Serverless and Managed Services: Cloud providers offer managed SQL databases with automatic scaling, high availability, and minimal management overhead. Conclusion: SQL’s Legacy and Future From its inception in the research labs of IBM to its current role in cloud and hybrid architectures, SQL has proven to be remarkably resilient and adaptable. SQL remains foundational to data management due to its flexibility, readability, and robustness. While NoSQL and other data technologies have found their niches, SQL continues to be the dominant choice for relational data storage and analytics, proving that the language and its foundational relational model are here to stay. As data continues to grow in volume and complexity, SQL is expected to evolve, incorporating new technologies while maintaining its core principles. SQL’s ability to balance innovation with reliability has solidified its place as a mainstay of database technology, ensuring its role in the data-driven future. Read the full article
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Structured Query Language (SQL) is the most popular language used in computers to create and manage databases. It is a language which has its own syntax and grammar. It does not belong to a particular company but is a universal language. The Structured Query Language can be pronounced Sequel or SQL. Like other computer languages like C, C++, Pascal, Java etc. We need a way to use it on our computer. We need a program that uses SQL as its means of communication. SQL is monitored by an independent organization, but each company adds a few features to its own implementation. MySQL is an application which is getting increasingly popular. The increasing popularity indicates that it is good, efficient, effective and reliable. In a simple manner, SQL is a non-procedural English-like language which processes data in groups of records rather than one record at a time. A few functions of SQL are the following: Storage of data Modification of data Retrieval of data Data deletion Generation of tables and other database projects. How Hard Is It To Learn SQL SQL is database layer query language and is not very difficult to learn. It does not require any prior programming experience to learn SQL queries. Learning SQL can be really easy if you already know a programming language. The fastest way to learn SQL is to start learning by doing it. History Of SQL A paper styled “A Relational Model of Data for Large Shared Data Banks” by Edgar F. Codd wrote in 1970 defined the relational database model. It became the basis for developing the SQL. Codd was a researcher associated with IBM. Based on his findings, in 1974 IBM began working on a new language for relational database management systems. The new language was originally called SEQUEL, or Structured English Query Language. The language went through a few modifications, implementations and the name was also changed a few times before it was finally called SQL. Subsequently, many SQL-based offerings hit the market where IBM had a key role to play. SQL is a language which is easy for beginners to learn than other programming languages like Java, C++, PHP or C#. Some of the relational database management systems which use SQL are Oracle, Sybase, Microsoft SQL Server, Access, Ingres etc. Most database systems use SQL. Most of them have their own proprietary extensions that are usually used only on their system. “Select”, “Insert”, “Update”, ”Delete”, “Create” and “Drop” are the standard SQL commands which can be used to achieve almost everything that one needs to do with a database. For those students who want to learn to programme from scratch, many free online courses will be of help. Step 1: Strong Determination To Learn Not every person loves SQL and hence, many of your friends and family will try their level best to discourage you from learning the language. It is true that the world of programming is flooded with different competing languages and it is not really possible to pick the one which is the best. A language which works perfectly for you might not serve the same purpose for someone else. Hence, instead of paying attention to what the critics of SQL have to say, you must focus all your attention on learning the language you picked. Know About Types Of Jobs And Skill Required For SQL Here are some of the positions that require applicants to have SQL skills: Database Developer The database developer should have the experience and the skills such as with Spring, XML, PL/SQL, Apache Camel, and Agile Methodologies. He or she also should have the ability to work closely with applications and web developers. Excellent problem-solving skills and strong relationship management skills are added advantage. Database Administrator (DBA) The database administrator should have the ability to with the computers that have the data. He should understand how computers store and retrieve data and also should have the knowledge to create a database. And the knowledge of database
organization and how it affects the computer and network performance is a must for this position. Also must have the ability to solve the technical problems which are caused by the database design and malfunction. Data Analyst The database analyst should have technical and soft skills. Technical skills mean a basic knowledge of statistics to a rigorous understanding of Machine Learning and the computer skills such as a Statistical Language (R, SAS, SPSS), a scripting Language (Python, Matlab), a Spreadsheet (Excel), and Querying Language (SQL, Hive, Pig). The soft skills needed are; defining problem, knowing the audience and the delivery. Data Warehouse Engineer Data Warehouse Engineer should have the ability to dealing with people and the knowledge various aspects of data warehousing on the areas such as Overall end-to-end data warehousing architecture, understanding of client/server, server-side computing architectures and the understanding of database optimization concepts for tuning data access queries SQL Reports Writer SQL Reports Writer should have the overall knowledge of SQL and good communication skills, and various computer applications which are necessary for this position. Step 2: Start Simple Learning SQL can be frustrating and require a lot of hard work on reading and practicing queries and commands. Do not try to do everything at the beginning. - Practice Basic SQL. - Take it slow and learn simple queries first, then move to complex query writing. - Watch some video tutorial. - Practice with SQL assignment, example, and coding. You can find academic SQL assignment help at assign code website in case you are stuck. Step 3: Install My SQL and My SQL Workbench Why MySQL We have chosen MySQL since its simple, free and easy to learn. You can start with any database of your choice (if easily available). The below steps would still help you. Installation My SQL database is an open source and freely available database. You can easily download the My SQL server and its client workbench for quickly getting started. Download and Install My SQL Community Edition Database Download and Install My SQL Workbench Step 4: Learn SQL Fundamentals It's important to learn the fundamental concept of SQL first. Once you know the basic you can do more advanced things on SQL easily. An Overview Of Relational Database A relational database system contains one or more objects that are called tables. The data for the database is stored in these tables. Tables comprise of rows and columns. Rows contain the records or data for the columns. Columns contain the column name, data type and any other attributes for the column. Selecting Data In order to query the database and retrieve selected data that match the criteria, the select statement is used. The column names which follow the select keyword determine which columns will be returned in the results. One can select as many column names as one wants or can use a “*” to select all columns. The table name that follows the keyword “from” specifies the table that will be queried to retrieve the desired results. The optional “where” clause indicates which data values or rows will be returned or displayed. It is done based on the criteria described after the keyword “where.” Create Table “Create table” statement is used for creating a new table. In order to create a new table, the keywords “create table” must be used followed by the table name, an open parenthesis, the first column name, the data type for that column, any optional constraints and a closing parenthesis in order. Use of an open parenthesis before beginning the table and a closing parenthesis after the table is crucial. Each column definition should be separated with a comma. All SQL statements must end with a semicolon. Insert Data To insert or add a row of data into the table the “insert” statement is used. The keywords “insert into” must be used to insert records into a table followed by the table name, an open parenthesis,
a list of column names separated by commas, a closing parenthesis, the keyword “values” followed by the list of values enclosed in parenthesis. The values will behold in rows and they will match up with the specified column names. Update Data For updating records the “update” statement is used. A “where” clause must be carefully constructed for this purpose. In order to delete records or rows from the table, the “delete” statement is used. If the “where” clause is left all records will be deleted. To delete a table and all rows in a table the “drop table” command is used. Drop table is different from deleting all the records in a table. Only column and constraint information remain when all of the records in the table are deleted. Table definition and all rows get removed when dropping the table. Step 5: Read Some Good Books from Experts Although you can learn a lot of things on the internet and web-based tutorials. I recommend you to pick best mysql book. My favorite book is MySQL Crash course, I highly recommended it for beginners. Step 6: Start Writing and Running Simple Queries Write simple queries on My SQL and observe the results. Some simple query exercise that you can try are listed below resources SQL Exercise By Stanford A course by Stanford University requires the students to do following exercises. SQL Zoo Tutorials This tutorial contains some basic exercise that you can start with. MySQL Exercises, Practice, Solution Step 7: Simple Is Not Enough: Try Complex Queries and Performance Improvements Once you feel comfortable on simple queries and practice exercises you can move to complex queries. At this stage, I will recommend you to start focusing on the performance aspect of queries. Try to write and query that perform better. There are many ways to write SQL query however the performance may change. You need to write the queries efficiently that can return results in a short time. Learning SQL is a very important step in developing our database skills. If one has all his data in the SQL database, he needs to know how to retrieve it properly. It is also essential to know how to leverage the power of SQL to perform advanced table joins and other complex queries. Databases can be manipulated using the Data Manipulation Language (DML) which is a subset of SQL. One will be able to learn how to create databases and tables, delete data from databases and comprehend other complexities such as NULL values. A very common use of SQL is to perform searches against large volumes of data. Searching is made easy with many operators of SQL. The users just need to be aware of the multiple options available and they should be able to decide which technique is the best for them in a given situation. These tips should be practiced on a regular basis especially when writing queries. Hi my dear friends, I am a freelance writer in ClazWork scholarship essay writing service. I have prepared the number of articles, assignments, projects, professional essays document, thesis papers etc. I have 4 years experience in M Phil thesis writing papers. All the fields of papers are available in our company. Recently I will publish the article name as “Learning Tips for using SQL”
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REVIEWING THE CHARTS: 03/04/2021 (Lil Nas X’s “MONTERO”, Mimi Webb, Russ Millions & Tion Wayne)
So, we have a #1 debut, and that’s pretty much the only story here in the UK Top 75 as we get a filler week before Demi Lovato, Olivia Rodrigo and Lil Tjay run in and cause havoc. As for now, “Wellerman” is replaced at the top by Lil Nas X’s controversial “MONTERO (Call Me by Your Name)”, spending its first week at #1 after making pretty sudden gains assisted by the video and alternate versions – the mid-week projection had this at #15. Elsewhere, we just see the fall-out from Bieber. Welcome back to REVIEWING THE CHARTS.
Rundown
It’s a quiet week – only seven new entries, and none from Rod Wave, 24kGoldn or AJR as I had predicted. That doesn’t mean there isn’t some stuff to talk about within the chart, or particularly off of the chart, as we have a fair few drop-outs switching their places with returning entries. In particular, we have Justin Bieber’s “As I Am” featuring Khalid being swapped out for “Anyone” at #25, as well as drop-outs for “Arcade” by Duncan Laurence – slightly premature, I’d think – and all of Lana Del Rey’s songs from last week. We also “Anxious” by AJ Tracey, “Heat” by Paul Woodford and Amber Mark and “Toxic” by Digga D exit the chart, but the only real notable loss was “34+35” by Ariana Grande ending its 21-week run on the chart. Returning to the Top 75 in its place – which I cover – we have “Mr. Brightside” by the Killers of course at #73, as well as “Midnight Sky” by Miley Cyrus at #72, “You’ve Done Enough” by Gorgon City and DRAMA at #70 (really hope this one becomes a hit) and “Don’t You Worry About Me” by Bad Boy Chiller Crew at #66. In terms of climbers and fallers, we do have some notable gains and losses. For songs travelling down the chart, we have “Patience” by KSI featuring YUNGBLUD and Polo G tanking a sharp drop in its third week to #18, “Streets” by Doja Cat shaking off the video gains at #22, “drivers license” by Olivia Rodrigo continuing to collapse at #27, another sharp drop for HVME’s remix of Travis Scott’s “Goosebumps” down to #34 probably due to ACR, which was probably the fate for “Get Out My Head” by Shane Codd at #46. The same probably can’t be said for Drake’s losses, as “What’s Next” is at #40, “Lemon Pepper Freestyle” featuring Rick Ross is at #41 and “Wants and Needs” featuring Lil Baby stalls at #55. We also see falls for “Money Talks” by Fredo and Dave at #50, “Bringing it Back” by Digga D and AJ Tracey at #51, “Sweet Melody” by Little Mix on its way out at #57, “Headshot” by Lil Tjay featuring Polo G and Fivio Foreign down to #61 off the debut (although it’ll rebound thanks to the album as soon as the next week rolls around), “Ready” by Fredo featuring Summer Walker at #62, “You’re Mines Still” by Yung Bleu featuring Drake at #63 and “Day in the Life” by Central Cee at #69. Where it gets interesting are our gains, such as outside the top 40 with “What Other People Say” by Demi Lovato and Sam Fischer which could very well get even higher next week thanks to the album. We also have “Track Star” by Mooski at #53 off of the debut and a couple of tracks entering the top 40 for the first time, those being “Heartbreak Anniversary” by Giveon at #39 and Majestic’s remix of “Rasputin” by Boney M. at #38. Elsewhere in the top 40, we have “Let’s Go Home Together” by Ella Henderson and Tom Grennan at #13 and two songs marking their first week in the top 10, those being “Little Bit of Love” by Tom Grennan at #10, a song continuing to sour on me, and “Your Love (9PM)” by ATB, Topic and A7S, an EDM song at #8 that I initially mocked for its soulless repackaging but has honestly got me pretty hooked since. I’m excited to see how this one does. For now, however, let’s get on with our new arrivals.
NEW ARRIVALS
#64 – “Cloud 9” – Beach Bunny
Produced by Joe Reinhart
Beach Bunny is a power pop band who last year released their album Honeymoon on Mom+Pop and it’s basically a modern r/indieheads staple in that it’s an accessible, airy pop-rock record fronted by a woman. It’s not anything unique, really, or different if you look further into it but that’s fine because there’s a lot of vaguely “indie” or music snob releases pushed out every year that miss the charts entirely. It’s a different story, however, when a year later, it gets viral on TikTok and streams its way onto the chart. In that case, we have “Cloud 9” by Beach Bunny, a pretty simple but sweet love song about a guy who just makes her feel a lot better about herself in times where she can’t pick herself up from the rut she’s in. Again, it’s a simple track but enhanced by the wonderful and unique vocal performance from front-woman Lili Trifilo and some pretty great production making sure no guitar lick is missed in this mix, especially in that chorus which is such an ethereal blend of the electric guitar dubs. I would argue that this actually should end at that second chorus even if it ends feeling abrupt as the transition to the final chorus feels a lot less cathartic than it does awkward, especially if the bridge is going to be a simplistic, quirky instrumental meander that doesn’t go far enough to be a guitar solo and hence feels kind of like a worthless addition. As is, this is a pretty great song still, just not the most fully realised once it loses that initial tight surf groove, though I’ll let it pass if we’re going to get rock this good on the charts again. I know this won’t really get more traction for Beach Bunny – or power pop for that matter – but more of this, please.
#52 – “You All Over Me” (Taylor’s Version) (From the Vault) (Remix) (feat. DaBaby) (Part 2) (Radio Edit) – Taylor Swift featuring Maren Morris
Produced by Taylor Swift and Aaron Dessner
Sadly, this does not feature DaBaby and is not the remix, radio edit or sequel to any previously released song. Jokes aside, I guess brackets are the next big comeback for pop music, which goes hand-in-hands with remixes and re-releases, hence why Taylor Swift is dusting off this leaked Fearless-era cut for a new recording with country singer Maren Morris, who you probably know from her contributions to Zedd’s “The Middle”. Now whilst Swift is a great songwriter, I do often find myself frustrated by how she treads common ground all too frequently without establishing much different with how a song is structured or how it emotionally connects. This is true not just lyrically but especially sonically as of recent, as despite being written in 2008, it has too much in common with the less interesting cuts off of folklore for me to really care that much. That’s especially if Taylor’s going to undercut the clean acoustic guitars with flourishes of harmonica and crow sound effects, showing some genuine intrigue here before refusing to let any of that develop past a couple stray melodies or notes further back in the mix. I’m trying really hard to be compelled by these re-recordings and re-releases of her back catalogue as I do consider myself a fan, but it’s tough to pay attention when any new compositions we get sound like folklore leftovers with Maren Morris only put to use as decoration, much like HAIM on “no body, no crime” – and we already got an album full of folklore leftovers. I’m not a fan of this, sorry – I can see the appeal, and I do think this has enough of a country tinge to it to make it at least somewhat interesting – but this goes in one ear and immediately out of the other.
#48 – “Tonight” – Ghost Killer Track featuring OBOY and D-Block Europe
Produced by Ghost Killer Track and Kenzy
Screw the formalities and screw the analysis because D-Block Europe are back to add another D-Block to their EU collection – and since they’re Londoners, their only – and that’s Paris, and contrary to the British nature, we’ve let French rap chart in the top 50 out of the fact that they collaborated with two of the most comical rappers in British history. They’ve also linked up with producer Ghost Killer Track, also from France, as this is ostensibly his song even if he intends not to prove himself with this dull piano-based beat and oddly-mastered bass and percussion, which are really just DBE staples. Unfortunately, past the initial comedy of that first line in the chorus, neither Young Adz or Dirtbike LB deliver any stupid lyrics or funny inflections, instead just resorting to being as boring as they can in their constant flexing as possible. I guess the French guy here, OBOY, commands a higher energy in his verse if only through his comical “no, no, no” ad-libs, but he’s the only French speaker in an otherwise basic British trap song that I just cannot see the appeal in when we’ve had song after song from these guys for three years now. This won’t be the last we see of cookie-cutter UK rap this week though so brace yourselves for that.
#47 – “Last Time” – Becky Hill
Produced by LOSTBOY
It’s almost as if the charts are trying to send me off to sleep as here we have Becky Hill, a singer hedging the line between a non-presence and mildly annoying, which is arguably more frustrating than downright infuriating as her slightly smokier voice does not sound bad, just lacking in texture in every way, especially if the multi-tracking is going to be this minimal on a royalty-free deep-house beat produced by Getty Images with a pretty worthless drop, a generic and simple melody of piano stabs for major chords, and a whole bunch of reverb on the vocal take... but it still ends up feeling dry as there’s nothing here to quench that thirst for a tighter, bass-heavy house banger or even a more ethereal, dreamy trance track, deciding to stick to a healthy medium of boring and utter garbage. Yes, that was a singular sentence. I’m not awake enough to form a cohesive sentence less than 40 words long, and this new Becky Hill track is just worsening that if anything. Speaking of...
#21 – “Body” – Russ Millions and Tion Wayne
Produced by Gotcha Bxtch
Who’s Russ Millions? He’s Russ. No, not that Russ. British Russ – or Russ Splash, stylised as Russ splash on Spotify and nowhere else. This confusingly-named fellow appeared on the charts a couple times and possibly most famously with “Keisha & Becky”, a song also featuring Tion Wayne that is referenced on this very track. Sigh, I usually like Tion Wayne but even he can’t be bothered to delivery his usual brand of suave charm or sinister menace, instead opting for a more growling but ultimately completely monotone cadence that doesn’t flatter him or Russ, who one of my friends described as sounding like one of the aliens from Toy Story. This is a pretty by-the-numbers drill beat too, and it’s pretty safe to say that neither Russ or Tion Wayne here are going to bother with wordplay, even when they start pretty smoothly trading bars and Tion Wayne goes for a more unique chopper flow in the second verse. This is just not of any note. Once again, speaking of...
#17 – “Good Without” – Mimi Webb
Produced by Freedo
I assumed Mimi Webb debuted this high because of a talent show she won or something because I’d never heard her name but instead, she just happened to have a major label deal before her unreleased song just happened to go viral on TikTok and just happened to be supported by one of the women who just happened to be the biggest creator on the platform. Yeah, and this song just happened to be garbage, suffering from every possible millennial pop trope and then some, from the mix dressed rather too overtly in reverb, the ugly guitar pluck, a generic indie-girl voice that you swear you’ve heard before in one of those dreadful piano covers of popular songs they use in adverts, as well as this ballad being undercut by badly-programmed trap percussion. I can tell this label is trying to create somewhat of an Olivia Rodrigo phenomenon from this and I for one am terrified of the Poundland knock-offs to come. Screw this.
#1 – “MONTERO (Call Me by Your Name)” – Lil Nas X
Produced by Roy Lenzo, Omar Fedi and Take a Daytrip
At least Lil Nas X will bring some passion into this chart week? Well, not really, as when I hear this I recall that Pitchfork review of his EP, a much-maligned critique that featured the ever-so pretentious questioning if Lil Nas X really enjoyed making and listening to music. It reminds me because I think I now fully get it – at least when Lil Nas X was making slap-dash pop rock with Travis Barker or meme-worthy country rap with Billy Ray Cyrus for less than two minutes apiece, there was something invigorating in the execution or at least in concept. That 7 EP is still not a bad debut at all, but this new single “MONTERO”, a long-anticipated record that went from constantly-teased demo to Super Bowl commercial to Satanic-panicked videos of Lil Nas giving Satan a lap-dance to own the conservatives, has the same remote dreariness to it as “HOLIDAY” did late last year. The acoustic, Latin-flavoured guitar loop reminds me of his much better track “Rodeo” from that aforementioned EP that used its energy for similarly lighthearted subject matter but with some genuine energy, a Cardi B feature and a lot less subtle moombahton creeping in. With that said, I can’t say Lil Nas X didn’t try, as his vocal performance, whilst largely insufferable and strained, gives some energy to an otherwise aggravatingly stunted beat, and makes it a lot more infectious than it has any right to be. Content-wise, the song is essentially about a full circle where Lil Nas X becomes increasingly desperate for a man who starts off lonely and in a bad place, and the irony is that Lil Nas gets more explicitly sexual and crazed due to a combination of the LA life-style surrounding him and the fact that he’s simply, for lack of a better term, “down bad”, despite the fact that this guy doesn’t seem particularly desirable. Lil Nas knows this, though, and acknowledges it in the pre-chorus where he outright says that this guy is living the cocaine-addled celebrity life, but not living it right without Mr. Bullriding and Boobies in his life. I’m happy about the video and the outrage it seems to cause not just within conservative spaces but also amongst the hip-hop community, particularly Joyner Lucas, and I’m pretty happy with how out and proud Lil Nas X is about his sexuality, even if it leads to lines like “Shoot a child in your mouth while I’m ridin’”. I’m just really not a fan of this song past its content, which could really be interesting but falls flat with this plucking production that wastes time in barely two minutes with humming interludes. It’s not bad at all, just not for me.
Conclusion
And that concludes our week, and wow, what a bad week this was for new arrivals. Admittedly, it’s a filler week so only “MONTERO (Call Me by Your Name)” will probably last – or at least we can hope as even if I don’t like the song, I still have to give out an Honourable Mention to someone, and it may as well be Lil Nas X trying to put the effort in. Best of the Week easily goes to Beach Bunny for “Cloud 9”, far and away the only good song here, with Worst of the Week also going out pretty easily to Mimi Webb’s “Good Without”, which is the type of soulless, unmemorable garbage that makes pop music look uninspired, and as a person who writes about the charts constantly, it’s a misconception I don’t want proven or revisited. Dishonourable Mention is a toss-up but I guess I’ll give it to Russ Millions and Tion Wayne for that sprinkle of drill disappointment that is “Body”, and that’ll be it for this week. I predict some impact from Demi Lovato, Lil Tjay and especially Olivia Rodrigo next week, but for now, here’s our top 10:
Thank you for reading – sorry for the grouchiness on this one – and I’ll see you next week!
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Netflix’s The Midnight Club Is Not a Midnight Mass Sequel (But There Is Cast Crossover)
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Between booze and cigarettes, says Mike Flanagan, he’s shed a lot of addictions by this point in his life, but work isn’t one of them. “I cannot eliminate work,” the writer-director tells Den of Geek and other press over Zoom. “That is the addiction I haven’t escaped and it’s running amok in the absence of all the others.”
He’s not kidding. In the last five years, Flanagan has directed, written or co-written and edited five feature films (Hush, Before I Wake, Ouija: Origins of Evil, Gerald’s Game and Doctor Sleep) as well as directing, co-writing and executive-producing three Netflix series (The Haunting of Hill House, The Haunting of Bly Manor and Midnight Mass) with producer Trevor Macy. Oh, and they’ve already wrapped filming on Netflix series number four, The Midnight Club, and at the time of writing, are currently prepping to fly back to Vancouver to start filming on Netflix series number five. That will be Something is Killing the Children, an adaptation of James Tynion IV and Werther Dell’Edera’s Eisner Award nominee comic book, and we hope to see it in 2023.
The last 18 months of all that, remember, happened during a pandemic that interrupted production on shows and films around the world, but still didn’t derail the Flanagan train. A break may finally be on the cards, says the writer-director, then concedes, “but every time I say that, I jump into something else.”
Underlying the compulsion to keep moving at this pace is anxiety, Flanagan explains. “There’s this fear that if you really shit the bed with a project, you won’t get another chance. So I like to start shooting another project before the first one comes out.” Flanagan’s most recent Netflix series Midnight Mass, is his most personal to date, and has been swimming around his head since the mid-2000s. His next series The Midnight Club goes back even further, as an adaptation Flanagan has dreamt of making since he was a teenager.
Read more
TV
Midnight Mass Is Creative, Bold, and Flawed Horror
By Nick Harley
TV
Why Midnight Mass is Mike Flanagan’s Most Personal Work
By Alec Bojalad
Flanagan was 16 years old in 1994, when Simon Pulse published The Midnight Club. Forget the James Patterson novel of the same name – there are no mobsters and psychopathic killers here. This is the story of Ilonka, Anya, Sandra, Kevin and Spence, five terminally ill teenagers at a hospice who come together each night at midnight to tell spooky stories, and make a pact that the first of them to die will try to make contact from beyond the grave. It’s a perfect fit for Flanagan, whose recent Netflix series have all combined well-turned scares with thoughtful contemplation of death and addiction.
Flanagan’s The Midnight Club anthology series won’t only adapt the spooky stories in the 1994 book, but also draw inspiration from across Christopher Pike’s work. The prolific author (whose real name behind the Star Trek-inspired pseudonym is Kevin McFadden) has a huge range of Young Adult and Adult stories to draw upon, from fan-favourite Sati to the ‘Thirst’ books, originally released as ‘The Last Vampire’ series, and many more.
A central cast of characters each telling their own scary stories means plenty of opportunity for guest cast cameos from the Flanagan rep company. From the cast of Midnight Mass, expect to see the actors behind Bev Keane, Riley Flinn, Sturge, Warren Riley, Dolly and Leeza Scarborough, respectively: Samantha Sloyan, Zach Gilford, Matt Bleidel, Igby Rigney, Crystal Balint and Annarah Shephard (formerly Cymone). They’ll be joined by Sauriyan Sapkota, Adia, Ruth Codd, Aya Furukawa, William Chris Sumpter and Nightmare on Elm Street’s Heather Langenkamp.
We’ll bring you more on The Midnight Club, which should arrive in 2022, and Something is Killing the Children, which is due to follow in 2023, when announced. For Flanagan’s sake, perhaps afterwards he’ll finally take that well-deserved break, before being welcomed back refreshed and ready for more.
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Midnight Mass is available now to stream on Netflix.
The post Netflix’s The Midnight Club Is Not a Midnight Mass Sequel (But There Is Cast Crossover) appeared first on Den of Geek.
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SQL
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Introduction DBMS (Database management system) uses a database languages, which is called databases languages. Database languages are used to represent schema, physical layout of data. Structured Query language (SQL) is data sub-language used to organize, retrieve and manage data from relational database, which is mapping RDBMS. The SQL language is defines as “Query Language”. It contains many other capabilities besides querying database. It includes features for defining the structure of data, for modifying data in database, and for specifying security constraints. History of SQL SQL has established as the standard relational database language. The origin of SQL and the development of relational database has same evolution path. Dr. E. F. Codd, an IBM Researcher, developed relational database concept in June 1970’s. SQL was developed at IBMS’s San Joss Research Laboratory in the early 1970s as a database language for RDBMS. This language originally called SEQUEL, was implemented as part of R project. The sequel language has evolved since then, and it name has changed to SQL (Structured Query Language).There are numerous version of SQL. In 1986, The American National Institute (ANSI) and International Standard Organization (ISO) published an SQL standard, called SQL-86 that was the updated in 1989 to SQL-89. Both standards were criticized as incomplete. These standards did not allow anyone to alter the database; you could not create a new table or assign a new user. Read the full article
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#SQL Nedir? Açılımı #Structured #Query #Language şeklindedir ve Yapılandırılmış Sorgu Dili anlamına gelir. Türkçe isminden de anlayacağınız üzere SQL bir programlama dili değildir. SQL bir sorgulama dilidir. SQL’e ait komutları anlayıp derleyebilen veritabanı sistemlerinde (RDBMS ve DBMS) verileri işlemenize imkân sağlar. . #SQL Ne İşe Yarar? SQL ile veritabanına kayıtlar ekleyebilir, var olan kayıtları güncelleyebilir, istenmeyen kayıtları silebilir, tüm kayıtları veya belli şartlara uyan özel kayıtları listeleyebiliriz. Bu işlemler temel CRUD (Create, Read, Update, Delete) işlemleridir. Bunların dışında veritabanı sisteminize göre başka işlemler de yapabilirsiniz. . #SQL Tarihçesi SQL’in tarihçesi kısmında Wikipedia sitesindeki İngilizce metinden tercüme yaparak bilgi vermenin daha doğru olacağını düşünüyorum. SQL 1970’lerin başında IBM’de Donald D. Chamberlin ve Raymond F. Boyce tarafından geliştirildi. İlk zamanlarda SEQUEL (Structured English Query Language) adıyla IBM San Jose Araştırma Laboratuvarı’ndaki bir grubun 1970’lerde geliştirdiği IBM’in orijinal ilişkisel veritabanı yönetim sisteminde (System R) saklanan verileri işlemek ve almak için tasarlandı. Daha sonra “SEQUEL” İngiltere merkezli Hawker Siddeley uçak şirketinin ticari markası olduğu için SEQUEL kısaltması SQL olarak değiştirildi. 1970’lerin sonunda, Relational Software Inc (şimdiki Oracle Corporation) Codd, Chamberlin ve Boyce tarafından tanımlanan kavramların potansiyelini gördü ve kendi SQL tabanlı RDBMS’lerini ABD Deniz Kuvvetleri, Merkezî İstihbarat Teşkilatı ve diğer ABD devlet kurumlarına satma arzuları ile geliştirdi. Haziran 1979’da, Relational Software Inc. VAX bilgisayarları için piyasada bulunan ilk SQL, Oracle V2 (Sürüm2) uygulamasını piyasaya sundu. IBM sistemin kullanışlılığını ve pratikliğini belirlemek için müşteri test sitelerinde SQL’i test ettikten sonra System/38, SQL/DS ve DB2 de dahil olmak üzere System R prototipine dayalı ticari ürünler geliştirmeye başladı ve sırasıyla 1979, 1981 ve 1983 yıllarında piyasaya sürdü. (Istanbul Province) https://www.instagram.com/p/Bx7UkICh07E/?igshid=ftv9bmqogbut
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Brief history on the relational database and SQL. No theory or tech details. Don Chamberlin and Ray Boyce created SQL based on Ted Codd’s relational model theory.
❤ Codd’s motto: “Tell me what you want, not how to find it.”
Ray and I thought that Codd’s relational ideas were great, but they had one flaw. Codd was trained as a mathematician, and he framed all his concepts in mathematical terms. He never talked about tables. He called them relations. He defined a “relation” as “a subset of the Cartesian product of a set of domains.” He proposed two languages, called the Relational Algebra and Relational Calculus. Both were full of mathematical symbols, like existential and universal quantifiers. These symbols were puzzling to non-mathematicians, and couldn’t be typed on a keyboard.
Ray and I thought that the essential beauty and simplicity of Codd’s ideas were obscured by all this math terminology.
We designed a language that we called SEQUEL: Structured English Query Language. We called the data structures tables, not relations. We used simple English keywords like SELECT FROM WHERE that are easy to understand and type. The basic ideas were Codd’s, but we framed them in terminology that anyone could understand.
Ray and I wrote a paper about the SEQUEL language. Part of the mission of IBM Research is to contribute to science, and IBM had no product plans based on SEQUEL at the time, so they allowed Ray and I to publish our SEQUEL paper at a technical conference in Ann Arbor, Michigan in May 1974.
Ray and I flipped a coin to decide who would get to go to Ann Arbor, and Ray won the toss. At the conference in Ann Arbor, Ray got to see the famous debate between Ted Codd and Charlie Bachman, comparing Codd’s relational approach with Bachman’s navigational approach. I would have loved to see this discussion. I think it was the last time that anyone seriously tried to defend the concept of a navigational database. Starting in 1974, I think the writing was on the wall that relational databases were the future of database management.
One month after the Ann Arbor conference, my friend Ray died suddenly of a brain aneurysm at age 25. He left behind a wife and one-year-old daughter. My family has stayed in touch with Ray’s wife and daughter for the last forty years; camping every summer. Ray’s daughter Kristin is now a manager at a data security company.
Now Prove It
Work continued at IBM Research to prove the concept of an RDBMS. The project to build a relational prototype was called “System R.” I was one of the managers of this project. We had a talented team of about 12 IBM programmers. A similar team was put together at UC Berkeley, called the Ingres project, under the leadership of Prof. Michael Stonebraker. Their objective was the same as ours: to prove the concept of an RDBMS. The Berkeley team based their prototype on another high-level query language called QUEL.
Both the System R project and the Ingres project at Berkeley were successful and resulted in commercial products that became available in the late 1970s and early 1980s. The commercial version of SEQUEL took the shorter name, SQL.
The 1970s and 80s were an extraordinary time in the history of computing. The price of computers had fallen to the point where nearly all companies and many other organizations were converting their records from paper and putting them into computers. As a result, there was a large market for database systems, and Relational systems were ready to fill the bill.
Larry Ellison's startup, Oracle
I think one thing tipped the balance in favor of SQL. A young man named Larry Ellison had dropped out of the U. Chicago and come to CA in the hope of making some money in computer software. This was an unproven concept in the 1970s when most software was free. But Larry read the paper Ray and I had published on the SEQUEL language, and he thought that it represented IBM’s future database strategy.
Larry decided to implement SEQUEL on a minicomputer so that he could sell an IBM-compatible database product for less than IBM would charge for the same language on a mainframe. Larry’s startup company was much faster and more nimble than IBM, and in fact, his SEQUEL implementation beat IBM’s to market by about two years. Larry’s company, which is now called Oracle, became very successful selling SQL systems to the U.S. Government—so successful, in fact, that the government released something called FIPS 127
#don chamberlin#sql#sequel#relational database#programming#programming languages#database#raymond boyce#charlie bachman#ted codd#ibm research#rdbms#larry ellison#oracle#system r#michael stonebraker#uc berkeley#ingres
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In the 1960s and 1970s he worked out his theories of data arrangement, issuing his paper "A Relational Model of Data for Large Shared Data Banks"[3] in 1970, after an internal IBM paper one year earlier.[15] To his disappointment, IBM proved slow to exploit his suggestions until commercial rivals started implementing them.[citation needed]
Initially, IBM refused to implement the relational model to preserve revenue from IMS/DB[citation needed]. Codd then showed IBM customers the potential of the implementation of its model, and they in turn pressured IBM. Then IBM included in its Future Systems project a System R subproject – but put in charge of it developers who were not thoroughly familiar with Codd's ideas, and isolated the team from Codd.[citation needed] As a result, they did not use Codd's own Alpha language but created a non-relational one, SEQUEL. Even so, SEQUEL was so superior to pre-relational systems that it was copied, in 1979, based on pre-launch papers presented at conferences, by Larry Ellison, of Relational Software Inc, in his Oracle Database, which actually reached market before SQL/DS – because of the then-already proprietary status of the original name, SEQUEL had been renamed SQL.
via Wikipedia
IBM being IBM in the seventies.
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Database
Database Fundamentals must be prepared to all the computer professionals and users. If you lack in their moderno meaning of terms, you would always find an uneasiness and discomfort when these jargons come to you. This article is targeted to novice and expert both, so that novice can prepare and an expert can revise things as well. My approach is to mention all the things concerned with database concepts.
[1] Entity and Entity Relationships :
Entity :
An Entity is place, object or thing for which we can collect information.
Such as Student is an Entity and we can collection information like Name, Phone and Address. Here, Name, Phone and Address are the Attributes of entity \'student\'.
Entity Relationship Diagram :
Also called as E também-R Diagram. E também-R Diagram is the graphical depiction of the entity, its attribute and relationship between entities.
[2] Data and Database :
Data :
Data are the single unit of an information.
Such as if name of an employee is \'John\', then \'John\' is data. His telephone . is \'+9109880959786\', then, this is also data. The value of the attribute of any entity can be said as data.
So, Data are the known facts that can be recorded and have their implicit meaning. e também.g. name, telephone, address etc.
Data is variado and \'Datum\' is the um form of the data.
Information :
When the set of data are collected together in meaningful manner, an information is generated.
Such as if we take example of an employee \'John\'. The Name is \'John\' , Telephone . is \'+9109880959786\' , designation is \'DBA\'. So, if we collectively analyze these, we get information that \'John\' is an employee with telephone . \'+9109880959786\' and he is designated as \'DBA\'.
So, When the desapareces set of data are collected together, information get produced. Although, this information is not for computer, this is just for humans only.
Database :
Database is the collection of related data.
Database is logically coherent collection of data with desapareces inherent meaning. random assortment of data can not be said as database. Such as Telephone Diary is also database, but, if it is randomly stored then, it can not be said as database. Database can be generated manually or in computerized manner. The Library catalog is also database.
[3] Database Management System (DBMS) :
Database Management System is the collection of programs and tools that enables users to create and maintain the database.
DBMS is also general purpose utilitário system that facilitates the process of defining, constructing and manipulating databases for various applications.
Characteristics of Database Management System :
(1) Self Describing
(2) Insulation from Programs and Data Abstraction
(3) Support of Multiple views to Database.
[4] Advantages of DBMS:
1- Controlling Redundancy :
There are provisions in all database models that redundant storage of the data can be avoided.
2- Security Over Unauthorized Access :
This is the feature found in the database that without proper login, one can modify or store database. The security can not be achieved with the flat file (Sequential) approach.
3- Providing Persistent Storage for Database Objects :
Database can be used as the persistent storage of Program objects, Database and Database structures. This meant that complex object of programming languages can be stored in the database. This gives more flexibility and compatibility of database over the programming languages.
4- Permitting Inferencing and Actions using Rules :
Inferencing is the method for defining deducing rules for inferencing new information from stored database. Such database are called as Deducible Database. In other words, there must be desapareces methods to provide information by logical implementation disponível the stored database.
6- Allowing Multiple User Conexão :
DBMS has the capability to provide concurrent execution of various parts of the database. In this approach, Deadlock and other anomalies are also handled by the DBMS.
5- Backup and Recovery :
Database Management Systems have proper mechanism to Backup the whole database and recover when any disaster comes to picture. There are methods for Disaster Recovery in all DBMS.
[5] Data Models :
data model is the set of conceptual tools for describing data, their relation, semantics and consistency constraints. There are following data models-
(1) Hierarchical Model
(2) Network Model
(3) Relational Model
(4) Object Relational Model
Describing all of these would be out of context. You should know that with all these, Relational Model is famous one. Newer implementation of DBMS do follow Object Oriented Model. Such as Oracle, Sybase and SQL Server.
[6] Logical and Physical Data Independence :
Data Independence is the quality of DBMS that ensure the capability to change the database in manner that the change in one level does not affect the other level. Such as change in the physical storage (Internal Level) does not affect the database structure (Conceptual Level).
(1) Logical Data Independence:
Capability to change the Logical structure without changing the external and internal schema of the database.
(2) Physical Data Independence:
Capability to change the Physical schema without any change in the conceptual schema of the database.
[7] Database Languages :
There are following database languages-
[1] DDL (Data Definition Language)
[2] DML (Data Manipulation Language)
[3] DCL (Data Control Language)
[1] DDL (Data Definition Language)
This is the language concerned with the creation of database structure and schema related with this. This language is concerned with the definition of the whole database architecture. DDL is used to define and manage all the objects in an database. Such as creating Databases, creating security objects that define the whole database.
[2] DML (Data Manipulation Language)
Insertion, Incremento , Delete and Selection are the activities concerned with the database manipulation language. DML is used to Select, Insert, Incremento, and Delete data in the objects defined using DDL.
[3] DCL ( Database Control Language)
Database control language is concerned with the consistency maintaining, authorizing access and other control over the database.
There are desaparece other languages which must be known. These are -
VDL (View Definition Language) : Providing means to view the conceptual schema of database for external level of three level schema.
SDL (Storage Definition Language) : Providing means to change or modify the internal schema of the database.
[8] Relational Database :
The Relation database model is based upon the conception of implementing the database with the Mathematical Set Theory. In this model, data is collection of tables called Relation in the set theory. The Tabular representation of data contains rows and columns in which rows represent set of attributes of individual entity and the columns represent the attribute of entity.
model is also said as Relational Database Model, if it follows complete set of Rules defined by Dr. E também.F. Codd. There are 12 Rules of Dr. Codd. In all of them, only Oracle is supposed to follow nearly all of them. But, the best in performance is Sybase which is more easier to configure that of Oracle.
SQL :
SQL is actually Structured Query Language. This is pronunciated as \'sequel\', but \'Ess-Que-El\' is also correct. It was initially named by Dr. E também.F. Codd who named it Structured English Query Language (S E também Que L ) as Sequel.
SQL is based acessível the Relational Model. Nearly all the database implementation in the world are in Relational Model. Sybase ,SQL Server, Oracle, DB2 are the famous implementation of Relational Model. But these are also kept in the Category of Object Relational Model. Microsoft Access is not supposed to be relational model. This actually uses desapareces flavors of relational database. But, can not be taken into account of pure Relational database.
ANSI-SQL :
American National Standards Institute handles the standards of SQL. The changes are made time to time. We have ANSI-SQL-89, ANSI-SQL-92 and other standards. There are several levels decided. Microsoft SQL Server is given entry level.
Conclusion :
This is all about providing protection for passwords. There are many other things to research in the same scenario and I would like to share my ideas when such studies are complete. Overall, my aim was to open your eyes that backups are not only to secure your data, but due to carelessness this may lead to leakage of information. In my opinion, disclosure of important information is more serious matter than loss of information. So, awareness is important and there is little effort to apply in securing your backups.
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