When 1+1=1: That Impossible Connection
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About — Tango is About the Connection™
Please try again later. Kindle Edition Verified Purchase. Gabriela doesn't hold back sharing from all parts of her life experience and from her heart. Quotes, poetry and dialogue are wise, sensual, romantic, and provide an infinite amount of information toward continued growth.
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Worthy of countless rereads and referrals. A must read for anyone seriously interested in the art of tango. And the concepts are very much applicable to everyday life I have read many books on loving relationships and I have danced Tango Argentino for more than 15 years, in which time I have visited Buenos Aires three times.
What is so amazing about this book is the author's ability to use such simple English and occasionally Spanish, whilst she glides almost imperceptibly between tango and relationships, touching on recognized philosophical concepts for good measure. Certainly the best I have ever read on relationships and to be commended to both dancers and teachers of tango.
One of my favorites on connection. One of my favorites on connection! A lovely book filled with gentle insights, depth and wisdom. Unlike several other tango books by women, this one is not angry or strident. Nice book, well organized in small sections, which is very suitable for the topic. Very honest and on occasions with depth. It is different from other books because it covers many aspects of the Tango life, with good explanations and observations.
It is worth reading. One person found this helpful. I have to admit, it is a little bit embarrassing for a man my age to find so much wonderful advice in a book by a woman half my age, but there it is. Condrea's wonderful little book is specifically about argentine tango but almost everything she says it true general as well. I could give examples, like "You are free to say 'yes' and you are free to say 'no'," but out of context they sound like cliches. If table A has a ton of updates and table b has a ton of reads or has a ton of updates from another application , then table A's locking won't affect what's going on in table B.
Others bring up a good point. Security can also be a good reason depending on how applications etc. I would tend to take a different approach, but it can be an easy way of restricting access to certain data. It's really easy to just deny access to a certain table in a pinch. My blog entry about it. The data relationship may be technically 1: So if you have twenty million rows and there's some set of values that only exists for 0. Your question can be interpreted in several ways, because of the way you worded it.
The responses show this.
There can definitely be 1: No question about it. The "is a" relationship is generally one to one.
I did mean to use it, in its connotation, of being a rare thing. Life is about the energy we share - a gaze, an embrace, a fleeting exchange of irreplicable moments - so subtle yet so powerful; life is about the connection. Person and Address don't bind so tightly. This pack of 10 postcards gives you 10 excuses to write someone you haven't talked to in a while, someone you miss, even someone you see every day Dark matter, you know, of something. You would typically want the blob to be in a separate table to improve lookups of the non-blob data.
A car is a vehicle. One car is one vehicle. One vehicle might be one car. Some vehicles are trucks, in which case one vehicle is not a car. Several answers address this interpretation. But I think what you really are asking is In other words, should you ever have two tables that contain exactly the same keys? In practice, most of us analyze only primary keys, and not other candidate keys, but that question is slightly diferent. Normalization rules for 1NF, 2NF, and 3NF never require decomposing splitting a table into two tables with the same primary key.
Off the top of my head, I'm going to guess that the answer is no. There is a level of normalization called 6NF. The normalization rule for 6NF can definitely result in two tables with the same primary key. This is important to some, but not all, database designers. I've never bothered to put a schema into 6NF. There are reasons other than normalization for splitting tables. Sometimes split tables result in better performance.
With some database engines, you can get the same performance benefits by partitioning the table instead of actually splitting it. This can have the advantage of keeping the logical design easy to understand, while giving the database engine the tools needed to speed things up. I use them primarily for a few reasons.
One is significant difference in rate of data change. Some of my tables may have audit trails where I track previous versions of records, if I only care to track previous versions of 5 out of 10 columns splitting those 5 columns onto a separate table with an audit trail mechanism on it is more efficient. Also, I may have records say for an accounting app that are write only. You can not change the dollar amounts, or the account they were for, if you made a mistake then you need to make a corresponding record to write adjust off the incorrect record, then create a correction entry.
I have constraints on the table enforcing the fact that they cannot be updated or deleted, but I may have a couple of attributes for that object that are malleable, those are kept in a separate table without the restriction on modification. Another time I do this is in medical record applications. There is data related to a visit that cannot be changed once it is signed off on, and other data related to a visit that can be changed after signoff. In that case I will split the data and put a trigger on the locked table rejecting updates to the locked table when signed off, but allowing updates to the data the doctor is not signing off on.
Another poster commented on 1: Say I have an employee table and the primary key is their SSN it's an example, let's save the debate on whether this is a good key or not for another thread. In a 3rd normal form database the column should depend only on the key, meaning the employee, but it actually depends on employee and type, so a 1: It also prevents overly sparse tables, if I have 10 columns that are normally filled, but 20 additional columns only for certain types.
- Die drei ???, Tal des Schreckens (drei Fragezeichen) (German Edition).
- When 1+1=1: That Impossible Connection - Gabriela Condrea - Google Книги;
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Most of the highly-ranked answers give very useful database tuning and optimization reasons for 1: Please note one important characteristic of the database implementation of most of these examples: That is, these relationships are 1: If the database designer wants to record changes in the relationship participants over time, then the relationships become 1: M; they lose their 1: With that understood, here goes:. This category is when one entity is a specific type of another entity. For example, there could be an Employee entity with attributes that apply to all employees, and then different entities to indicate specific types of employee with attributes unique to that employee type, e.
Doctor, Accountant, Pilot, etc. This design avoids multiple nulls since many employees would not have the specialized attributes of a specific subtype. Other examples in this category could be Product as supertype, and ManufacturingProduct and MaintenanceSupply as subtypes; Animal as supertype and Dog and Cat as subtypes; etc. Note that whenever you try to map an object-oriented inheritance hierarchy into a relational database such as in an object-relational model , this is the kind of relationship that represents such scenarios.
If those rules apply, then you have a 1: The same kind of relationship occurs if there is only one store as the headquarters of a company, or if only one city is the capital of a country, for example.
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Some kinds of scarce resource allocation , e. A colleague gave me this example recently. Marriage at least in legal jurisdictions where polygamy is illegal: I got this example from a textbook that used this as an example of a 1: For example, a car rental system might record a reservation in one entity, and then an actual rental in a separate entity. Although such a situation could alternatively be designed as one entity, it might make sense to separate the entities since not all reservations are fulfilled, and not all rentals require reservations, and both situations are very common.
I repeat the caveat I made earlier that most of these are 1: So, if an employee changes their role in an organization, or a manager takes responsibility of a different department, or an employee is reassigned a vehicle, or someone is widowed and remarries, then the relationship participants can change. If the database does not store any previous history about these 1: But if the database records historical information such as adding start and end dates for each relationship , then they pretty much all turn into M: There are two notable exceptions to the historical note: First, some relationships change so rarely that historical information would normally not be stored.
For example, most IS-A relationships e. Thus, the historical record point is moot; these would always be implemented as natural 1: Second, the reservation-rental relationship store dates separately, since the reservation and the rental are independent events, each with their own dates.
Since the entities have their own dates, rather than the 1: Let's say you want to store large images in a database typically, not the best way to store them, but sometimes the constraints make it more convenient. You would typically want the blob to be in a separate table to improve lookups of the non-blob data. In real databases it's sometimes useful to keep a rarely used field in a separate table: Rather than using views to restrict access to fields, it sometimes makes sense to keep restricted fields in a separate table to which only certain users have access.
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I can also think of situations where you have an OO model in which you use inheritance, and the inheritance tree has to be persisted to the DB. For instance, you have a class Bird and Fish which both inherit from Animal. In your DB you could have an 'Animal' table, which contains the common fields of the Animal class, and the Animal table has a one-to-one relationship with the Bird table, and a one-to-one relationship with the Fish table.
In this case, you don't have to have one Animal table which contains a lot of nullable columns to hold the Bird and Fish-properties, where all columns that contain Fish-data are set to NULL when the record represents a bird. Instead, you have a record in the Birds-table that has a one-to-one relationship with the record in the Animal table. There is a record size limitation on each record in the table. Sometimes tables are split in two with the most commonly queried information in the main table just so that the record size will not be too large.
Databases are also more efficient in querying if the tables are narrow. It's also a way to extend a table which is already in production with less perceived risk than a "real" database change. If you're using the data with one of the popular ORMs, you might want to break up a table into multiple tables to match your Object Hierarchy. Chapter 7 - Speak Without Words Chapter 8 - High Heels and Yellow Hippopotamuses Chapter 9 - The Rose is Just a Reminder Chapter 10 - Dance like Water Chapter 11 - Paint Outside the Lines Chapter 12 - A Reciprocal Relationship Chapter 13 - A New Flavor of Chocolate Chapter 14 - In the Mecca of Tango Chapter 16 - Like a Cat Chasing its Tail Chapter 17 - Take Your Sweet Time Chapter 19 - As Many Tangos Life lessons drawn from experiences on the dance floor, told in a casual, conversational tone, make this book suitable for people with absolutely no dance experience, as well as seasoned tanguer s.
It's about the connection we cultivate with those around us, with our partner, with ourselves.