I've read many information about IOT, and now in my head gruel...
Pls, help me solve question.
Have table, that have structure:
ID (PK); ID_DRUG_NAME (a); ID_FROM (b); ID_PROVIDER (c); DELETED;
The data from this table is never deleted but only marked that are removed.
Many queries uses ID, another queries uses a,b or a,c or a,b,c.
I want recreate this table using operator ORGANIZATION INDEX.
How it will be profitable?
How to rightly create a primary key and indexes?
What pitfalls do I get?
Index-organized tables (IOT) are best used when there is a single access-path. You've identified two different lead columns, so an IOT is probably not a good choice.
The issue here is that, if you make it an IOT, you have to choose one of the two columns (ID or ID_DRUG_NAME) that you'll frequently be filtering on to index. Theoretically, you could still add a second index on an IOT, but it's almost always a bad idea. An IOT with a second index is typically performs worse than if the second index doesn't exist, even when querying against the column in the second index.
Related
I am trying to prepare DB design for APEX application. Requirement is as follows.
In Departments IR page, users are asking below columns
Number of employees in each department (Department may or may not have employees)
Primary Location for Department (Department can have multiple addresses and addresses are stored in other table, along with primary flag)
Alternative Manager's Email Address for Department (alt_manager_id column, this is optional column and refers to employees table)
I can implement these requirements using either inline sub queries or using OUTER JIONs. But, these approaches will have performance impact as the data grows (like 100s of thousands of rows). So, my question is, is it ok to store these data directly at "Departments" table and update "Departments" table when child tables gets updated. Basically, I am trying to store summary data at master table, instead of deriving it as on when needed from child tables. Is this considered bad practice? Is it ok to implement such DB design?
Thank you
"Is this considered bad practice?"
Usually yes. There are several problems with maintaining summary detail information in a master record.
Your inserts into child tables (and deletes if you have them) now also have to take a lock on the master record, to increment the count. This adds complexity to what should be simple transactions.
It also has two performance hits: the additional overhead of maintaining the counts and the potential for sessions to hang in multi-user environments.
Note that you are adding a definite performance hit to your insert activity for a possible saving in the performance of aggregating queries.
The good practice is to just run the counts when you need the summaries. Tune the queries if you need to.
If you think you really are going to be querying the summary data often enough for the workload to be a problem you should consider building materialized views for the summary queries. Then, when you enable query rewrites, Oracle will transparently query the materialized view if it can satisfy the query rather than re-running the aggregations. This is a technique which is used a lot in data warehouses, but there's no reason not to use it in OLTP environments if you really have the data volumes to justify it. Find out more.
Generally, try the simplest thing which could work first. Only look to do something different (like building a materialized view for aggregations) when you know you have a demonstrable problem with performance.
I assume the answer is "no" in this scenario, but I figured I'd ask and see if there was something I was missing:
I have an Oracle table which is partitioned for ease of data loading -- data is loaded into six separate tables and then partition-switched into the main table. The only thing differentiating these loading tables is the source of the data, so each one has a unique datasource column which is used to partition the main table. We occasionally have some ad hoc queries which look at this datasource in the main table, but the standard reports querying this table ignore this column entirely. Nothing insert/update/deletes individual records from this table, so there's no concern about updating any indexes.
In this case, is there any reason to use local indexes instead of global ones?
A local index makes a lot of sense - if you use partitioning for performance reasons.
If your queries always contain the partition key then a Oracle will only scan that specific partition (that is known as "partition pruning").
If you then have additional conditions that would benefit from an index lookup, the database only needs to check the local index which is much smaller then a global index and thus the lookup will be faster.
In your case, if you never (or almost never) include the partition key in the queries, you are right that the local index wouldn't be helpful.
I want to move some of my Azure SQL tables to Table storage. As far as I understand, I can save everything in the same table, seperating it using PartitionKey and keeping it unique within each partition using Rowkey.
Now, I have a table with a compound key:
ParentId: (uniqueidentifier)
ReportTime: (datetime)
I also understand RowKeys have to be strings. Will I need to combine these in a single string? Or can I combine multiple keys some other way? Do I need to make a new key perhaps?
Any help is appreciated.
UPDATE
My idea is to put data from several (three for now) database tables and put in the same storage table seperating them with the partition key.
I will query using the ParentId and a WeekNumber (another column). This table has about 1 million rows that's deleted weekly from the db. My two other tables has about 6 million and 3.5 million
This question is pretty broad and there is no right answer.
The specific question - can you use Compound Keys with Azure Table Storage. Yes, you can do that. But this involves manual Serializing / Deserializing of your object's properties. You can achieve that by overriding the TableEntity's ReadEntity and WriteEntity methods. Check this detailed blog post on how can you override these methods to use your own custom serialization/deserialization.
I will further discuss my view on your more broader question.
First of all, why you want to put data from 3 (SQL) tables into one (Azure Table)? Just have 3 Azure tables.
Second thought, as Fabrizio points out is how are you going to query the records. Because Windows Azure Table service has only one index, and that is PartitionKey + RowKey properties (columns). If you are pretty sure you will mostly query data by known PartitionKey and RowKey, then Azure Tables is perfectly suiting you! However you say that your combination for RowKey is ParentId + WeekNumber! That means that a record is uniquely identified by this combination! If it is true, then you are even more ready to go.
Next you say you are going to delete records every week! You should know that DELETE operation acts on a single entity. You can use Entity Group Transactions to DELETE multiple entities at once, but there is a limit of (a) All entities in batch operation must have the same PartitionKey, (b) The maximum number of entities per batch is 100, and (c) The maximum size of batch operation is 4MB. Say you have 1M records like you say. In order to delete them, you have to first retrieve them in groups by 100, then delete in groups by 100. These are, in best possible case 10k operations on retrieval and 10k operations on deletion. Event if it will only cost 0.002 USD, think about time taken to execute 10k operations against a REST API.
Since you have to delete entities on a regular basis, which is fixed to a WeekNumber let's say, I can suggest that you dynamically create your tables and include the week number in its name. Thus you will achieve:
Even better partitioning of information
Easier and more granular information backup / delete
Deleting millions of entities requires just one operation - delete table.
There is not an unique solution for your problem. Yes, you can use ParentID as PartitionKey and ReportTime as Rowkey (or invert the assignment). But the big 2 main questions re: how do you query your data, with what conditions? and how many data do you store? 1000, 1 million items, 1000 millions items? The total storage usage is important. But it's also very important to consider the number of transaction you will generate to the storage.
I have inherited a datababase with tables that lack primary keys. It's an OLTP database. One of the tables in question has ~300k records, and has no primary key implemented, even though examining the rest of the schema tells me one column is used AS a primary key, ie being replicated in another table, with identical name, etc. ie. This is not an 'end of line' table
This database also does not implement FKs.
My question is - is there ANY valid reason for a table (in Oracle for that matter) NOT to have a primary key?
I think PK is mandatory for almost all cases. Lots of reasons will exist but I'll treat some of them.
prevent to insert duplicate rows
rows will be referenced, so it must have a key for it
I saw very few cases make tables without PK (e.g. table for logs).
Not specific to Oracle but I recall reading about one such use-case where mysql was highly customized for a dam (electricity generation) project, I think. The input data from sensors were in the order 100-1000 per second or something. They were using timestamps for each record so didn't need a primary key (like with logs/logging mentioned in another answer here).
So good reasons would be:
Overhead, in the case of high frequency transactions
Necessity or Un-necessity in that case
"Uniqueness" maintained or inferred by application, not by db
In a normalized table, if every record needs to be unique and every field is referenced in other tables, then having a PK additionally adds an index overhead and if the PK would never actually be used in any SQL query (imho, I disagree with this but it's possible). But it should still have a unique index encompassing all the fields.
Bad reasons are infinite :-)
The most frequent bad reason which is actually responsible for the lack of a primary key is when DBs are designed by application/code-developers with little or no DB experience, who want to (or think they should) handle all data constraints in the application.
Any valid reason? I'd say "No"--I'm a database guy--but there are places that insist on using the database as a dumb data store. They usually implement all integrity "constraints" in application code.
Putting integrity constraints into application code isn't usually done to improve performance. In fact, if you built one database that enforces all the known constraints, and you built another with functionally identical constraints only in application code, the first one would almost certainly run rings around the second one.
Instead, application-level constraints usually hope to increase flexibility. (And, in the process, some of the known constraints are usually dropped, which appears to improve performance.) If it becomes inconvenient to enforce certain constraints in order to bulk load some scruffy data, an application programmer can just side-step the application-level constraints for a little while, then clean up the data when it's more convenient.
I'm not a db expert but I remember a conversation with a friend who worked in the Oracle apps dept. who told me that this was done to handle emergencies. If there was a problem in some report being generated which you could fix by putting in a row, db level constraints often stand in your way. They generally implemented things like unique primary keys in the application rather than the database. It was inefficient but enough and for them and much more manageable in case of a disaster recovery scenario.
You need a primary key to enforce uniqueness for a subset of its columns (useful if you need to refer to individual rows). It also speeds up certain queries because of the index associated to it.
If you do not need that index, or that uniqueness constraint, then you may not need a primary key (the index does not come free).
An example that comes to mind are logging tables, that just record some data (that is never updated or queried for individual records).
There is a small overhead when inserting to a table with an index and you need an index if you have a primary key. Downside of course is that finding a row is very costly.
I am developing an enterprise application with an Oracle backend. I am designing a core part of the DB architecture now and im having some questions on it.
First and most important thing is, most of my tables needs to preserve old data. For example
Consider a table with the fields
Contract No, Contract Name, Contract Person, Contract Email
I have a records like
12, xxx, yyy, xxx#zzz.ccc
and some one modifies it to
12, xxx, zzz, xxx#zzz.ccc
at any point of time i need to display the new record while still have copy of the old record.
So what i thought was to put a duplicate record of the old data and update the fields that was changed and have a flag to keep track of active records with something like "is active" as 1.
The downside is that this creates redundancy in the table and seems like a bad design. But any other model seems unnecessarily complex and this seems cleaner to me. Also i dont see any performance issues having a duplicate record too. So please let me know if this is ok or am i missing something here.
Some times where there is a one to many relationship my assumption is to have a mapping table where i map the multiple entity in individual records by repeating master ID and changing child ID in each record. Is this a right way to do it or is there a better way to do it.
Is there a book on database best practices.
Thanks.
The database im dealing with is Oracle 11g on a two node RAC cluster
Also i dont see any performance issues having a duplicate record too.
Assume you have a row that, over time, has 15 updates to it. If you don't store any temporal data (if you don't store different versions of the row), you end up storing one row. If you do store temporal data, you end up storing 15 rows.
You also need more indexes, because the id number is no longer sufficient to identify a single row.
If you have only relatively small tables, you probably won't see any performance difference. (There will be one, but it probably won't be noticeable to users.) But a table that has 10 million rows will perform differently than a table that has 150 million rows. (15 versions per row, times 10 million rows.)
Some times where there is a one to many relationship my assumption is
to have a mapping table where i map the multiple entity in individual
records by repeating master ID and changing child ID in each record.
Is this a right way to do it or is there a better way to do it.
You probably need to know which child rows belong to which parent rows. So you need more than a single master id for the key. The master id alone doesn't tell you which version of that row in the parent table applies to a given child row.
Is there a book on database best practices.
There are books on temporal databases. The first one that I know of is Snodgrass's Developing Time-Oriented Database Applications in SQL. It's available in several formats, and it's free. It's also kind of old, but the information in it is important to understand if you're going to be building a temporal database. Also, think about reading Date's book Temporal Data and the Relational Model.
Wikipedia has an article that summarizes the ideas behind temporal databases.
Is normalization completely mandatory.
That's a meaningless question. You will have different issues with tables normalized to 2NF than you'll have with tables normalized to 5NF or 6NF.
I would keep the old/history records in a separate table. Create an upd/del trigger to populate your audit/history table for you, and keep only the most current data in your main table.
See here for an example. Many other similar examples exists in SO.