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My knowledge of databases and SQL is based in most on university classes. Anyhow, I spent few monts (almost a year) in a company, where I was working with databases.

I have read few books and I have taken part in few trainings about databases such as MySQL, PostgreSQL, SQLite, Oracle and also few nonSQL dbs such us MongoDB, Redis, ElasticSearch etc.

As well as I said, I am begginer, with a lot of lacks of knowledge but today, someone told something, what is totally against my begginer's knowledge.

Let me explain. Let's take SQL database and create simple table Person with few records inside:

id | name   | age
-----------------
1  | Alex   | 24
2  | Brad   | 34
3  | Chris  | 29
4  | David  | 28
5  | Eric   | 18
6  | Fred   | 42
7  | Greg   | 65
8  | Hubert | 53
9  | Irvin  | 17
10 | John   | 19
11 | Karl   | 23

Now, it's the part, I would like to focus on - id is the INDEX.

So far, I thought it works in this way: when a table is being created the INDEX is empty. When I am adding new record to my table the INDEX is being recalculated based on some alghortims. For example:

Grouping one by one:

1    ... N
N+1  ... 2N
     ...
XN+1 ... (X+1)N

so, for my example with size = 11 elements and N = 3 it will be like this:

id | name   | age
-----------------
1  | Alex   | 24     // group0
2  | Brad   | 34     // group0
3  | Chris  | 29     // group0
4  | David  | 28     // group1
5  | Eric   | 18     // group1
6  | Fred   | 42     // group1
7  | Greg   | 65     // group2
8  | Hubert | 53     // group2
9  | Irvin  | 17     // group2
10 | John   | 19     // group3
11 | Karl   | 23     // group3

So, when I am using query SELECT * FROM Person WHERE id = 8 it will do some simple calculation 8 / 3 = 2, so we have to look for this object in group2 and then this row will be returned:

8  | Hubert | 53

enter image description here

This approach works in time O(k) where k << size. Of course, an alghoritm to organise rows in groups is for sure much more complicated but I think this simple example shows my point of view.

So now, I would like to present another approach, which has been showed me today.

Let's take once again this table:

id | name   | age
-----------------
1  | Alex   | 24
2  | Brad   | 34
3  | Chris  | 29
4  | David  | 28
5  | Eric   | 18
6  | Fred   | 42
7  | Greg   | 65
8  | Hubert | 53
9  | Irvin  | 17
10 | John   | 19
11 | Karl   | 23

Now, we are creating something similar to Hashmap(in fact, literally it is a Hash Map) which maps id to address of row with this id. Let's say:

id | addr 
---------
1  | @0001
2  | @0010
3  | @0011
4  | @0100
5  | @0101
6  | @0110
7  | @0111
8  | @1000
9  | @1001
10 | @1010
11 | @1011

So now, when I am running my query: SELECT * FROM Person WHERE id = 8

it will map directly id = 8 to address in memory and the row will be returned. Of course complexity of this is O(1).

So now, I have got few questions.

1. What are the adventages and disadventages of both solutions?

2. Which one is more popular in current database implementations? Maybe different dbs use different approaches?

3. Does it exist in nonSQL dbs?

Thank you in advance

ruhungry
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    in [tag:sql-sever] Primary Key are Clustered Indexes which are different from normal indexes on columns that are Non Clustered Indexes – Vladimir Oselsky Apr 04 '14 at 14:50
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    You may want to ask this question in Database Administrators as you could get more knowledgeable answers. – Vulcronos Apr 04 '14 at 14:59
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    Please do not cross-post. One question, in one site, is enough. If you posted at the wrong site, questions can be migrated. – ypercubeᵀᴹ Apr 07 '14 at 13:36

1 Answers1

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  1. What are the adventages and disadventages of both solutions?

The second solution can not perform range scans. It is great for selecting a single ID. But what if you want ids 3 through 8? It has to grab all the records individual which in the real world isn't just O(1) * 6 records to retrieve. In a large, production database with a HashMap index you would get records on different pages, requiring you to hit the disk and read six different pages into memory.

In a B-Tree structure, like how your first situation would actually be implemented, the ids would be sequential on disk and a single page would likely hold ids 3 - 8 increasing the speed of range scans will making individual access O(log n).

  1. Which one is more popular in current database implementations? Maybe different dbs use different approaches?

I don't have a huge experience in lots of different databases. I know Sql Server uses B-Trees mostly, but SQl 2014 has some new Hash Indexes you can use on certain table. I hear a lot of No Sql databases and caching databases built on retrieving individual records use hash indexes as well. This makes sense for caches since you want the record for user A Page 11 and don't need range scans.

  1. Does it exist in nonSQL dbs? Yes. Taking a quick look at the create index documentation for postgressql I see it supports both Hash and B-Tree indexes as well as a few others.
Vulcronos
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  • this post has been moved. Could you add you answer here http://dba.stackexchange.com/q/62576/36686 ? Thank you in advance :) – ruhungry Apr 07 '14 at 21:09