Relations as First-Class Citizen - A Paradigm Shift for Software/Database Interoperability

I'm happy to announce that Alf Alf 0.15.0 has just been released and with it, this web site! I've been thinking about all of this for many years, often as a cross-cutting concern in my (other) research work. I've been hacking on Alf in particular during my free time for more than two years now. I think it was time to share it in a slightly more official way than as an (almost invisible) open-source research prototype on github. Recent personal events gave it a serious boost and a few people convinced me to give it more visibility. So here we go.

Alf is a modern, powerful implementation of relational algebra. It brings relational algebra where you don't necessarily expect it: in shell, in scripting and for building complex software. Alf has an rich set of features. Among them, it allows you to:

Query .json, .csv, .yaml files and convert from one format to the other with ease,

Query SQL databases with a sounder and more powerful query language than SQL itself,

Export structured and so-called "semi-structured" query results in various exchange formats,

Query multiple data sources as if they were one and only one database,

Create database viewpoints (mostly read-only viewpoints for now), to provide your users with a true database interface while keeping them away from data they may not have access to,

Enjoy a rich set of relational operators and even define your own high-level and domain-specific ones.

Alf is very young and not all of the advanced features are stable and/or documented. I plan to spend some time in the next weeks and months to work on them, so stay tuned. In the mean time, you can play with Alf on this website, install Alf 0.15.0 and start playing with it on your own datasets and databases, in shell or in ruby. I'll come with advanced material on this blog as soon as possible, I promise.

The rest of this post explains the context of this work and why it exists in the first place, in the form of a (very accessible) scientific paper (this writing style is also a test, let me know what you think). The following section provides a short overview of the proposed approach, explaining the title of this blog post. We then detail Alf's proposal, first with a short example illustrating the advantages compared to existing solutions, then with a more theoretical presentation covering three main questions: why true relational algebra?, what type system to expose?, and why not classes and objects?. Alf's limitations and features to come are then briefly discussed, before concluding.

Yet another database connectivity library?

We already have ARel, Sequel, SQLAlchemy, Korma, jOOQ and probably hundreds of similar projects for connecting to databases from code. Do we really need one more?

Well, Alf is a database connectivity library but it is first and foremost about a proposal for a new kind of software/database interoperability, or a paradigm shift if you want. This paradigm is called Relations as First-Class Citizen and it makes Alf different from existing approaches. The difference lies in the kind of data abstraction exposed to the software developer:

Call-level interfaces (e.g. JDBC) expose SQL query strings and database cursors (e.g. java.sql.ResultSet ),

), Higher-level SQL libraries, such as ARel, Sequel, and jOOQ expose SQL queries as well. However, they abstract them behind abstract syntax trees (AST), and algebra-inspired manipulation operators.

Object-Relational Mappers (ORMs) expose classes and objects together with the SQL/AST interface they generally rely on (e.g. the symbiosis between ARel and ActiveRecord),

Alf and Axiom expose Relations (i.e. sets of tuples) and relational algebra. For those interested, I'll discuss some differences between Alf and Axiom later in this blog post. In the mean time and unless stated otherwise, what is said about Alf applies to Axiom too.

In this blog post, I'm going to compare Alf with the second category above, i.e. high-level SQL-driven libraries. Not because the Relations as First-Class Citizen paradigm cannot be compared to, say, Object-Relational Mapping but because, at first glance, Alf shares a lot more with those libraries than with ORMs. First things first thus, let start looking at those similitudes and (sometimes subtle) differences. We start with a motivating example in the next section before moving to more theoretical arguments in the one immediately following.

Motivating example

This might appear rude or offensive, but I need to start by complaining about existing approaches and libraries (why would I work on Alf in the first place otherwise?). Sequel is used in this blog post but the situation is similar with all the libraries I mentioned previously. I've chosen Sequel because I commonly use and actually love it. No offense to be taken therefore even if I claim, in essence, that things could be improved.

My main complaint is that, despite providing closure under operations, existing libraries fail at providing a truly composable way of tackling data requirements. To understand why, let me take a concrete software engineering example on (a slighly modified version of) the suppliers and parts examplar. We'll use the following suppliers and cities relations:

suppliers : cities : +------+-------+---------+--------+ +----------+----------+ | :sid | :name | :status | :city | | :city | :country | +------+-------+---------+--------+ +----------+----------+ | S1 | Smith | 20 | London | | London | England | | S2 | Jones | 10 | Paris | | Paris | France | | S3 | Blake | 30 | Paris | | Athens | Greece | | S4 | Clark | 20 | London | | Brussels | Belgium | | S5 | Adams | 30 | Athens | +----------+----------+ +------+-------+---------+--------+

Let suppose that the suppliers themselves are the software users and that the following requirements must be met by the particular inferface showing the list of suppliers to the current user:

A supplier may only see information about the suppliers located in the same city than himself. The supplier's status is sensitive and should not be displayed. The country name must be displayed together with the supplier's city

In terms of the query to be built, those requirements involve a restriction ( same city as ), a selection ( no status ) and a join ( with country name ). Suppose you are supplier S3 , the list of suppliers you see looks like this:

+------+-------+-------+----------+ | :sid | :name | :city | :country | +------+-------+-------+----------+ | S2 | Jones | Paris | France | | S3 | Blake | Paris | France | +------+-------+-------+----------+

Struggling with reuse and separation of concerns

Writting a monolithic query is rather straightforward. Using Sequel for instance:

requester_city = ... # from context (authenticated user) DB [ :suppliers ] . natural_join ( :cities ) . select ( :sid , :name , :city , :country ) . where ( :city => requester_city ) # => SELECT sid, name, city, country # FROM suppliers NATURAL JOIN cities # WHERE (city = ...)

In software involving complex requirements, relying on monolithic queries is unfortunately not always possible and/or desirable (otherwise, creating database views would simply be enough). Two main reasons explain this:

The same requirements tend to apply to various and independent software features. For instance, the first two requirements above might apply everytime a list of suppliers is shown, while the third one might not. Complex requirements generally call for a design that achieves both separation of concerns and reuse.

Complex software also involves context-dependent requirements. For instance, the first requirement above might be relaxed for administrators (say, suppliers with status greater than 30).

This explains why connectivity libraries and their SQL utilities exist in the first place: because of the need to build queries, often at runtime and according to some context. There is a desperate need for more support for this in DBMSs themselves. In the mean time, developers rely on the ability of host programming languages and third-party libraries.

Back to our example above, what about the following "design"?

# Meet 1) and 2) together as a utility method: separation of concerns def suppliers_in ( city ) DB [ :suppliers ] . select ( :sid , :name , :city ) . where ( :city => city ) end # Meet 3) as a utility method: separation of concerns def with_country ( operand ) operand . natural_join ( :cities ) end # Meet them all: composition and reuse requester_city = ... # from context with_country ( suppliers_in ( requester_city ))

Wrong. The original, and correct, SQL query was:

-- Give the id, name, city and country of every supplier located in city ... SELECT sid , name , city , country FROM suppliers NATURAL JOIN cities WHERE ( city = ...)

The new one seems smiliar, but is wrong. As shown below, we lost the country in the process:

-- Give the id, name and city of every supplier located in city ..., provided -- the city is known in `cities` SELECT sid , name , city FROM suppliers NATURAL JOIN cities WHERE ( city = ...)

What happened? In short, Sequel 's join does not correspond to a algebraic join of its operands. Instead, its specification looks like "adds a term to the SQL query's FROM clause", whose data semantics is far from obvious (here you can blame SQL itself). Observe in particular that the following algebraic equivalence does not hold in Sequel , preventing us from using the design above:

suppliers . natural_join ( cities ) . select ( :sid , :name , :city , :country ) <=!=> suppliers . select ( :sid , :name , :city ) . natural_join ( cities . select ( :city , :country ))

Join is a striking example of the problem at hand, but others exist that involve different operators. Let me insist on something: the same is true with ARel, Sequel, SQLAlchemy, Korma, jOOQ to cite a few. The fact is:

SQL has not been designed with composition and separation of concerns in mind,

Avoiding strong coupling between subqueries tends to be very difficult in practice,

Coupling hurts separation of concerns and software design.

To be fair... There is a way to use SQL (and, sometimes, those libraries) so as to avoid the problem described here. It amounts at using SQL in a purely algebraic way. Unfortunately, that way is not idiomatic and leads to complex SQL queries, that may have bad execution plans (at least in major open-source DBMSs). In the example at hand, using Sequel's from_self in a systematic way (e.g. on every reusable piece) is safe from the point of view of composition and reuse:

def suppliers_in ( city ) DB [ :suppliers ] . select ( :sid , :name , :city ) . where ( :city => city ) . from_self end def with_country ( operand ) operand . natural_join ( :cities ) . from_self end requester_city = ... # from context with_country ( suppliers_in ( requester_city )) # SELECT * FROM ( # SELECT * FROM ( # SELECT sid, name, city FROM suppliers # WHERE (city = ...) # ) AS 't1' # NATURAL JOIN cities # ) AS 't1'

The complete recipe for using SQL in such a "safe" way is more complex, of course, but possible. I won't provide the details in this blog post, let me know if a dedicated one is welcome. For now, let see how our new paradigm helps.

Relation Algebra at the rescue...

Libraries like Sequel and Arel offer closure under operations, meaning that you can chain operator invocations (e.g. operand.select(...).where(...).where(...) ). Subtly enough, that does not make them exposing an algebra, because SQL is not itself a pure relational algebra (see later) and these libraries do espouse SQL in a rather faithful way.

In contrast, the Relations as First-Class Citizen paradigm aims at providing an interface that is designed for composition and reuse. To achieve this, Alf takes some distance from SQL and exposes a true relational algebra instead, inspired from Tutorial D. This makes a real difference, even if subtle. To convince yourself, I invite you to use Alf's Try console to check that the example below works as expected. As shown, the three requirements of our case study can be incorporated incrementally thanks to the true composition mechanism offered by an algebra. Commenting a line amounts at ignoring the corresponding requirement:

requester_city = 'Paris' solution = suppliers # 1). A supplier may only see information about the suppliers located # in the same city than himself. solution = restrict ( solution , city : requester_city ) # 2) The supplier's `status` is sensitive and should not be displayed. solution = allbut ( solution , [ :status ] ) # 3). The country name must be displayed together with the supplier's city. solution = join ( solution , cities )

Try!

To better understand why it works, observe that in Alf, the equivalence mentionned in the previous section holds. That is, the two following queries are equivalent, something that you can check by yourself using the console:

project ( join ( suppliers , cities ), [ :sid , :name , :city , :country ] )

Try!

and

join ( project ( suppliers , [ :sid , :name , :city ] ), project ( cities , [ :city , :country ] ))

Try!

Interestingly enough, this kind of equivalences may be used for query optimization and smart SQL compilation. I invite you to check the Optimizer and Query plan tabs of the console on both queries. The generated SQL query is the same in both cases. Alf tries very hard to keep generated SQL as simple as possible, in the hope to avoid ugly query plans in the SQL DBMS itself:

SELECT t1 . sid AS sid , t1 . name AS name , t1 . city AS city , t2 . country AS country FROM suppliers AS t1 INNER JOIN cities AS t2 ON ( t1 . city = t2 . city )

... plus extra

What if the cities tuples (that does not actually exists in the original suppliers and parts examplar), come from somewhere else? A .csv file, another database or whatever datasource?

requester_city = 'Paris' solution = suppliers # 1) and 2) above, but inline solution = allbut ( restrict ( solution , city : requester_city ), [ :status ] ) # Might be Relation.load('cities.csv'); we use a literal for execution on try-alf.org third_party_cities = Relation ( [ { city : 'London' , country : 'England' }, { city : 'Paris' , country : 'France' } ] ) solution = join ( solution , third_party_cities )

Try!

The example above shows that, in addition to the advantages previously cited, the composition mechanism of relational algebra, unlike SQL queries, makes few assumptions about where the operands come from, by very nature. In a sense, the Relations as First-class citizen can be seen as a purely functional kind of programming where immutable values are relations and functions are relational operators. This kind of comparison is not new. It was already suggested several years ago in Ben Moseley's famous Out of the Tar Pit essay. Alf contributes an example of the general framework outlined there.

More about the paradigm and its motivation

Moving from SQL to a relational algebra is one of the changes underlying the Relations as First-Class Citizen paradigm for software/database interoperability, but it is not the only one and maybe not the most important (?). The following subsections detail the paradigm further and provides motivations and theoretical arguments. They address the three following questions:

Why relational algebra is a better choice than relational calculus for developing software?

What type system do we want to expose to software developers? SQL's one or the host language's?

Why relations instead of traditional classes and objects for structural concepts?

From Relational Calculus (SQL) to Relational Algebra

In my opinion, the fact that SQL is used daily by software developers is the result of an historical mistake, or a misfortune at least. Indeed, SQL has been invented in the database community at a time where it was envisioned that end users would query relational databases. This is more than 40 years ago. At that time, the nature of software, software engineering, requirements engineering and human-software interactions were not understood as they are today.

With this envisioned reality in mind, SQL has been chosen nearer to (tuple) relational calculus than to relational algebra (for the sake of accuracy, it is a strange mix of both; yet another obscure historical reasons explain this). For a good understanding of the discussion here, it is important to understand the difference in nature between a calculus and an algebra:

In a calculus, what you describe is the problem to solve, not how to solve it. Hence the from ... select ... such that ... declarative kind of question you ask to an SQL DBMS: -- Get the cities where at least one supplier is located, provided -- at least one part is located there too. SELECT DISTINCT city FROM suppliers AS s WHERE EXISTS ( SELECT city FROM parts AS p WHERE s . city = p . city )

In contrast, with an algebra you manipulate symbols, that denote values, through a predefined set of operators. You use those operators to build or reach the solution to your problem: # Get the cities where at least one supplier is located, provided # at least one part is located there too. cities_from_suppliers = project ( suppliers , [ :city ] ) cities_from_parts = project ( parts , [ :city ] ) intersect ( cities_from_suppliers , cities_from_parts ) Try!

As shown by the example above, a calculus is more declarative than an algebra. In other words, the latter looks more like an algorithm. This explains why SQL, probably the most idiomatic end-user query language ever, has been designed as a calculus. As an end-user, when you (manually) query a database you generally know the problem at hand. Therefore, you welcome a declarative language since it allows you to express that problem while leaving to the underlying engine the job of finding the solution instead of having to describe the algorithm to compute it. This is what SQL offers to its users.

Now, I suppose it is not too risky to claim that, today, a large majority of interactions with databases is done by software components, possibly on behalf of their end users, and generally in accordance to specific requirements. The actual users of (relational) databases are not end-users after all, but software components and, indirectly, their developers.

Yet, developping software is of a very different nature than querying databases. As a software engineer, you generally don't have one single problem at hand. Instead, you have a set of problems called requirements and you find a design that allows meeting them all (cfr. the previous section for an example). One of the most effective strategies available in the software engineer toolset is divide and conquer. A modular design, for example, helps achieving a good separation of concerns with respect to those requirements while ensuring that the software behaves as expected when all modules are put together.

While the declarative style of programming of SQL is very nice for solving very specific and well isolated sub-problems in your requirements & design space, it is of almost no aid for putting the architectural pieces together. Yet, putting the pieces together is something software engineers do every single day. And so is writing algorithms. Exposing a relational algebra therefore appears more natural when it comes to software development, and when it comes to manipulating data vs. querying database. To be fair, libraries such as ARel, Sequel, and jOOQ already show the way: they provide an API that is closer to relational algebra than relational calculus. Alf and Axiom simply go further this path by abstracting from SQL and choosing a sound algebra known as Tutorial D as a better inspiration than SQL towards the same objective.

The Relations as First-Class Citizen paradigm makes all of this more sound in my opinion, because putting relations together is much easier than putting SQL queries together (cfr. the join example in the previous section). The semantics of "putting together" is more straightforward in the former case, that's all. An algebra is about providing operators for putting operands together, a calculus simply is not. Approaches such as Alf's is no less expressive, quite the contrary. For instance, expressing a SQL WHERE NOT EXISTS is kind of a nightmare with existing approaches, and almost impossible to do in a modular way due to the coupling between the main query and the sub-query:

# Show suppliers that supply no part at all (Sequel) DB [ :suppliers___s ]. where ( ~ DB [ :shipments___sp ]. where ( Sequel . qualify ( :sp , :sid ) => ( Sequel . qualify ( :s , :sid ))) . exists )

It is dead simple in Alf (and here, you can thank Tutorial D, where this operator comes from):

# Show suppliers that supply no part at all (Alf) not_matching ( suppliers , shipments )

Try!

Now, relational calculus and relation algebra are known to be equivalent in expressive power. This is what allows Alf to compile queries in the second form above to something similar to the former one and to send it to an underlying SQL DBMS. The feature is limited by the ability to reconcile the Ruby and SQL type systems though, something I will discuss in the next section.

From SQL's to Host's Type System

There is another very important change I have not discussed so far regarding the proposed Relations as First-Class Citizen paradigm. In essence, it is a challenging proposal (from an implementation point of view at least): why not abstracting from SQL completely?

Aside: this section applies to Alf but, as far as I know, not to Axiom.

Indeed, almost all approaches (even ORMs) do actually espouse SQL in a very rigid way. An obvious example is that the developer is almost never allowed to express filtering conditions or to perform computations that are not supported by SQL in the first place. It is unfortunate, because SQL's type system is old, and poor (few support for user-defined types, for instance). How about providing a query interface that actually espouse the host type system, i.e. the one of the host programming language (here, Ruby)?

Want to express a filtering condition involving a ruby regular expression? No problem:

# Get suppliers whose name contains a 'J' or a 'B' restrict ( suppliers , -> ( t ){ t . name =~ /J|B/ })

Try!

Want to compute an array-valued attribute (or even use you own user-defined data type/class)? No problem:

# Get suppliers and the letters of their name in uppercase extend ( suppliers , letters : -> ( t ){ t . name . upcase . chars . to_a })

Try!

Want to group tuples as sub-relations? There is even an operator for that:

# Get suppliers grouped by city group ( suppliers , [ :sid , :name , :status ] , :suppliers )

Try!

This might look at simply providing a consistent interface for working with relations. Absolutely, that's the point. You can mix everything, composing queries in the idiomatic way. In the example below, Alf compiles the 'Paris' restriction to SQL while it computes the 'letters' extension itself (see the optimizer and query plans), even if the extension comes before the restriction:

rel = extend ( suppliers , letters : -> ( t ){ t . name . upcase . chars . to_a }) rel = restrict ( rel , city : 'Paris' )

Try!

Now think about it. This amounts at abstracting from SQL and letting developers think in terms of their usual type system. While powerful, this is very challenging (but fun) in practice for the implementer (i.e. for me) and comes at a cost (for you). There are drawbacks and limitations that you must be aware of (I'll come back to this point in the next section). That means that you can't abstract from reality entirely after all, as often with abstractions, but yet more than with existing approaches in my opinion.

From One-At-a-Time to Set-At-a-Time

This point is very important, since it introduces a significant difference with Object-Relational Mapping. I haven't talked much about ORM so far, but it's true that Relations as First-Class Citizen is better compared to Object-Relational Mapping (ORM) than to libraries such as Sequel . Both are paradigms that present data to the software in a particular way, and provide an abstraction mechanism above SQL. (I take this opportunity to put a bit of fairness back into the picture. This is especially important for me since Alf itself currently relies on Sequel to generate cross-DBMS SQL code in a very easy way.)

Object-Relational Mapping relies on the availability of an Object Model, that aims at capturing the (structual) domain. Doing so is one interpretation of what Domain Driven Design (DDD) is about, more accurately one implementation strategy of DDD. I'm not convinced it's the good one, but it's definitely one of them. There are at least two reasons why I'm not convinced.

First, modeling the (data) domain is certainly not the same as designing a software for meeting requirements in that domain (whatever that means). The fact that you've drawn O-O diagrams (even if it's in your head) capturing the domain entities, their relationships and interactions is not sufficient for stating that the software implementation must be a copy-paste of those diagrams. Most of the time, the software supports the domain; it does rarely implement or simulate it. Models are there to guide your understanding of the domain, not to be the implementation of your requirements. Subtle difference (abstract one, I'm affraid), but important.

The second reason is more directly relevant to the proposed paradigm and Alf. Suppose a Supplier class in your O-O software. What does that class capture? Well, from a modeling point of view it captures the fact that supplier is a relevant concept/entity in the domain. From the software point of view, it captures an irrelevant set, and lots of individuals of (marginal?) interest:

The Supplier class captures the set of all possible suppliers, that is, all possible supplier instances that you can represent in software memory by invoking the class constructor. Observe that you can't do anything relevant with this set with respect to your actual requirements, except maybe "selecting" a particular individual.

class captures the set of all possible suppliers, that is, all possible supplier instances that you can represent in software memory by invoking the class constructor. Observe that you can't do anything relevant with this set with respect to your actual requirements, except maybe "selecting" a particular individual. Those individuals are of course not the real suppliers, but only information about them or a representation of them in the software. I invite you to read a previous writing of mine to understand why I think that manipulating information through individuals is just wrong.

I won't repeat those arguments here. Let me instead simply state a few requirements in our hypothetic suppliers and parts software, while highlighting relevant parts for the discussion at hand:

A supplier may only see information about the suppliers located in the same city than himself ,

, The GUI shall display relevant information about the supplier such as her name, city and country .

. The GUI shall never expose supplier statuses , except to administrators , that is, suppliers with a status greater than 30 .

, except to , that is, . The software should periodically send an email to all suppliers who supply less than 5 parts to ...

to ... The administration interface shall display performance indicators such as the number of registered suppliers per city , ...

such as the , ... and so on.

Hence the following question. Why does our source code provide such a huge visibility to completely irrelevant sets, e.g. the Supplier class, instead of promoting those relevant sets above as first class citizen? Hence the name of the paradigm, Relations as First-Class Citizen, because relations better capture those sets than O-O classes:

extend ( DEE , # the suppliers located in the same city than himself (say S3) visible : -> ( t ){ matching ( suppliers , project ( restrict ( suppliers , sid : 'S3' ), [ :city ] )) }, # administrators, i.e. suppliers with a status greater than 30 administrators : -> ( t ){ restrict ( suppliers , gte ( :status , 30 )) }, # registered suppliers registered : -> ( t ){ suppliers })

Try!

(Note that the example above does not aim at illustrating an actual user-friendly syntax or idiomatic way of implementing the kind of features I'm discussing here. It shows, in contrast, that all those relations can be captured rather easily, even all at once; try it).

ORMs such as Active Record provide so-called scopes that may be argued providing what I ask here (possibly with a better syntax, by the way):

class Supplier < ActiveRecord :: Base scope :administrator , -> { where ( "status > 30" ) } end

Two main important differences exist, though:

First, observe that in Active Record, Supplier and Supplier.administrator do not denote similar things. The first one is a Class , the second is an ActiveRecord::Relation and you can't substitute one for the other. In addition, scopes are subordinated to classes, making them second-class, not first-class citizen.

and do not denote similar things. The first one is a , the second is an and you can't substitute one for the other. In addition, scopes are subordinated to classes, making them second-class, not first-class citizen. Second, scopes do not allow deriving new first-class concepts. They mostly allow filtering existing ones (loosely speaking). For instance, you'll have a hard time trying to promote the concept below as first-class with scopes. Indeed, it would require creating "derived classes", whatever this is supposed to mean in practice: # performance indicators, e.g. registered suppliers per city indicators = summarize ( suppliers , [ :city ] , nb : count ()) # first-class means you can use it as any other concept restrict ( indicators , gt ( :nb , 1 )) Try!

To summarize (sorry if it seems offensive, I'd better like to be thought-provoking instead): ORMs promote irrelevant sets as first-class and a subset of relevant ones as second-class, subordinated to the former. Isn't that very strange? In addition, ORMs promote a "design around structural concepts" kind of programming style, where good object-oriented design focuses on behaviors instead.

Now, Alf provides a good foundation for Relations as First-Class Citizen, but it does not completely reach that point so far. Indeed, it provides a way to compute any relation and use it consistently. To implement the paradigm completely, however, it would also need to provide a way to 'promote' the relations that makes more sense in the domain as special citizen in the software design. I'll say a word about domain-specific relational operators and database viewpoints in the next section, which are good attempts to reach this but require more work.

Limitations and ongoing work

The approach proposed here opens an avenue for further optimization, experimentation and research. I close this blog post with an overview of my own ongoing work in this area (which are all subjects I will be talking about here in the near future). I also draw the reader's attention on Alf's current limitations.

Towards high-level, domain-specific relational operators

The closure property of relational algebra opens the ability to define new relational operators in a very simple way, provided they are shortcuts over longer expressions. Alf comes with such a facility, as illustrated below:

# It relation `test` contains at least one tuple return `then_relation`, # otherwise return `else_relation` def ite ( test , then_relation , else_relation ) union ( matching ( then_relation , project ( test , [] )), not_matching ( else_relation , project ( test , [] ))) end # It there are at least one Red part, show suppliers in London, otherwise # show suppliers in Paris ite ( restrict ( parts , color : 'Red' ), restrict ( suppliers , city : 'London' ), restrict ( suppliers , city : 'Paris' ))

Try!

While the example above is contrived, our experience suggests that the ite relational operator proves very useful in practice when dealing with complex data visibility and privacy requirements. Interesting enough, you can check that the compilation involves only one SQL query sent to the underlying DBMS, resulting in important performance improvements compared to other approaches relying on an if/then/else statement in the host language (especially when the latter is much slower than the DBMS engine itself, e.g. Ruby vs. a DBMS engine implemented in C).

Similarly, even when involving complex data types and collections, most query plans involve a constant number of SQL queries, avoiding the 'N+1 queries' trap infamously known with Object-Relational Mappers:

join ( suppliers , group ( join ( shipments , parts ), [ :sid ] , :supplied_parts , allbut : true ))

Try!

Alf already has a few high-level operators such as matching or page. The next release should include a few others currently evaluated on case studies: ite , image , abstract , dive , quota , etc.

Database viewpoints

The closure property of relational algebra also opens the ability to define composable database viewpoints. Viewpoints provide a very effective abstraction mechanism for implementing complex security/privacy requirements, as well as providing context-aware database interfaces.

Without entering the details here, the following example illustrates the approach by hacking on Ruby's super mechanism. Suppose we want to provide a database viewpoint on suppliers and parts located in London:

# Start of the viewpoint def suppliers restrict ( super , city : 'London' ) end def parts restrict ( super , city : 'London' ) end def shipments # restore foreign keys given the previous restrictions matching ( matching ( super , parts ), suppliers ) end # End of the viewpoint # Query as usual. This is entirely transparent. # Check it yourself, supplier S2 no longer exists in this viewpoint. restrict ( shipments , sid : 'S1' )

Try!

Database viewpoints are currently read-only in Alf. I intentionnally left the question of database updates aside in this blog post. Alf comes only with a very experimental interface for updates (cfr. Alf in Ruby) but a lot of work is still needed in this area.

Reconciling heterogeneous type systems

As already suggested, abstracting from SQL is challenging for the implementer. More specifically, abstracting from SQL and guaranteeing soundness and efficiency at the same time are conflicting requirements. Alf has a smart compiler that delegates to underlying engines what can be delegated, but the explicit use of the host type system is a showstopper during compilation. To better understand this, consider the following query:

restrict ( extend ( suppliers , uppercased : -> ( t ){ t . name . upcase }), city : 'Paris' , uppercased : 'JONES' )

Try!

If you take a look at the query plan, you'll observe that the restrict invocation is only partially compiled to SQL. The uppercased attribute is computed by Alf in Ruby and cannot be translated back to the SQL engine. This has serious performance implications, of course. As of current Alf version, this is the case as soon as you use a ruby block (e.g. ->(t){ ... } ).

All other approaches I'm aware of either have a similar problem or forbid such queries in the first place (and are hence less expressive). This calls for further symbiosis and interoperability between heterogeneous type systems (SQL and Ruby in the present case).

Conclusion

Arrived here? Kudos. To summarize, I'm convinced that Relations as First-class citizen provides better abstractions than existing approaches for software-database interoperability, or more generally, for handling the data manipulation subset of our software engineering requirements. In particular, I hope to have shown how current database connectivity approaches hurt separation of concerns and reuse (more generally, software design) and why favoring pure relational algebra over (idiomatic) SQL helps avoiding the trap.

As I've discussed, Alf itself needs more work to truly embrace the paradigm, as that goes further that simply providing an algebraic query language. Stay tuned, I'll provide more material and writings about how to use Alf in more complex software (such as the viewpoints stuff). In the mean time, any question or contribution (of any kind) can be adressed by sending an email to Bernard Lambeau (see the About page; I'm easily found on the Internet too). I'm currently looking for contributors both in the academics and in the industrial world for discussing, enhancing, testing and evaluating the approach, don't hesitate to contact me by email.

Acknowledgements

I'd like to thank Sergio C., Erwin S., Enrico S., David L., Magnus H., Kim M. and Louis L. for their feedback and comments on earlier versions of this blog post.