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I have a requirement to gather what are the database data changes or schema changes occurred after executing a nightly batch. For example there is a table employee which has two records. After nightly batch suppose one record inserted and one record updated. I want to capture what record is updated and what record is inserted. I am using Oracle database. I am looking for a script to do this as we have some issues to get licenses for new tools that does this task. So anyone can advise how this can be done programatically or using Oracle 11g built in functions? Any sample code is greatly appreciated.As we have large number of tables, I am looking for a generic way to do this.
Thanks
I would suggest using triggers on the changes you want to capture and inserting that information into another table that captures those changes.
There's some info right here in stackoverflow the best way to track data changes in oracle
If triggers are not a viable option, look into INSERTing into 2 tables at once, one being your target table and one being you logging/change capture table.
Here is an example on stackoverflow
Oracle INSERT into two tables in one query
A third option would be table auditing. See the following on stackoverflow
Auditing in Oracle
In OLTP systems, you can add audit columns in the table create_date, update_date or last_modified_time, transaction_type.
With create_date, update_date - you can set default sysdate to create_date and then you need to modify application logic to update update_date. Trigger also will work, instead of changing code at the small cost of performance.
With last_modified_time, transaction_type - you need to update those 2 fields on insert or update as part of your application logic or using trigger.
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I have a table for booking system and I want to apply a certain constraint that should be atomic. Simply, I just want to conditionally insert a row into that table. I don't want to read-prepare-write because it will cause race conditions. I decided to insert an initial row then update it with a sub-query condition and check affected rows count.
affectedRowsCount will always be 1 on concurrent requests which indicates a race condition. I know that isolation level of Serializable and lock mechanisms will help but I want to discuss other less strict ways
Pseudo Code
Start transaction
Insert single row at table Reservations (Lets call Row)
affectedRowsCount = Update Reservations where ID = "Row".id AND (SELECT COUNT(*) FROM "Reservation" WHERE ...) < some integer
if (affectedRowsCount === 0) throw Already Reserved Error
Commit transaction
There is no way to do this except
using SERIALIZABLE transaction isolation
locking everything in sight to serialize operations
It is unclear what exactly you are trying to do, but perhaps an exclusion constraint on timestamp ranges can help.
In general, the way to prevent other queries from having access to a row(s) for locking purposes is to use SELECT FOR UPDATE. I'm not sure if you're using postgresql or sqlite, but you can read about the postgresql functionality here. Sqlite does not support it.
The idea is that you can lock the row you for which are interested, and then do whatever operations you need to without worrying about other queries updating that row, and then commit your transaction.
A common scenario for this would be when you're trying to book a reservation, as it looks like your example may be doing something along those lines. We would do a SELECT FOR UPDATE on the row containing the resource we want to book, then check the available dates the user is wanting to book, and once we have ensured that the dates are available for that resource, go ahead and book it. The SELECT FOR UPDATE prevents the possibility of other people trying to book the same resource at the same time we are.
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I am building a Data Warehouse on SQL Server and I was wondering what is the best approach in handling the current record in a dimension table (SCD type 2) with respect to the 'end_date' attribute.
For the current record, we have the option of using a date literal such as '12/31/9999' or specify it as NULL. The dimension tables also have an additional 'current_flag' attribute in addition to 'start_date' and 'end_date'.
It is probably a minor design decision but just wanted to see if there are any advantages of using one over the other in terms of query performance or in any other way?
I have seen systems written both ways. Personally, I go for the infinite end date (but not NULL and the reason is simple: it is easier to validate that the type-2 records are properly tiled, with no gaps or overlaps. I prefer only one validation to two -- the other being the validation of the is_current flag. There is also only one correct way of accessing the data.
That said, a system that I'm currently working on also publishes a view with only the current records. That is handy.
That system is not in SQL Server. One optimization that you can attempt is clustering so the current records are all colocated -- assuming they are much more commonly accessed. You can do this using either method. Using a clustered index like this makes updates more expensive, but they can be handy for optimizing memory.
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I have been given an 800 lines SQL Query which is taking around 20 hours to fetch around 400 million records.
There are 13 tables which are partitioned by month.
The tables have records ranging from 10k to 400 million in each partition.
The tables are indexed on primary keys.
The query uses many inline views and outer joins and a few group by functions.
DBAs say we cannot add more indexes as it would slow down the performance since it is an OLTP system.
I have been asked to convert the query logic to pl/sql and then populate a table in chunks.Then do a select * from that table.
My end result should be a query which can be fed to my application.
So even after I use pl/sql to populate a table in chunks,ultimately I need to fetch the data from that table as a query.
My question is, since pl/sql would require select and insert both, are there any chances pl/sql can be faster than sql?
Are there any cases where pl/sql is faster for any result which is achievable by sql?
I will be happy to provide more information if the given info doesn't suffice.
Implementing it as a stored procedure could be faster because the SQL will already be parsed and compiled when the procedure is created. However, given the volume of data you are describing its unclear if this will make a significant difference. All you can do is try it and see.
I think you really need to identify where the performance problem is; where the time is being spent. For example (and I have seen examples of this many times), the majority of the time might be in fetching to 400M rows to whatever the "client" is. In that case, re-writing the query or as PL/SQL will make no difference.
Anyway, once you can enumerate the problem, you have a better chance of getting sound answers, rather than guesses...
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Each of the salesmen should make a forecast of his sales. I know how he may input data directly from Excel sheet to SQL table. Do I need to create different tables - one table per salesman? At the end I need to aggregate all the forecasts. Is it possible to make it with just one table?
The condition is that one salesman is not allowed to see the other salesmen forecasts.
It seems to be a common problem of inputting data to database by many different users with restrictions on access.
Update. Each salesman is in different town. Say we have 500 salesmen so it is not the way to gather data from 500 Excel files into one big Excel file and then load it to SQL.
actually you don't need to create different tables for each salesmen. one table is enough to load all your salesman info Excel data. to find each salesmen's forecast sales simple transmission query will help u
You need at least two tables. You need a staging table to receive the excel data and perform the necessary validation, transformation, etc. You need at least one table for data storage. Given that you are talking about people and sales, you probably want a normalized database. If you don't know what that means, I've heard good things about the book, Database Design for Mere Mortals.
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MSSQL database. I have issue to create database using old databases data. Old database structure is thousands tables conected with each other by ID. In this tables data duplicated many times. Old database tables have more than 50 000 rows (users). Structure like this table
Users (id, login, pass, register-date, update-date),
Users-detail (id, users_id, some data)
Users-some-data (id, users_is, some data)
and this kind of tables is hundreds.
And the question is, which design of db structure to choose, one table with all of this data, or hundreds of tables separated by some theme.
Which type of db structure would be with better performance?
Select id, login, pass from ONE_BIG_TABLE
or
Select * from SMALL_ONLY_LOGINS_TABLE.
Answer really depends on the use. No one can optimize your database for you if they don't know the usage statistics.
Correct DB design dictates that an entity is stored inside a single table, that is, the client with their details for example.
However this rule can change on the occasion you only access/write some of the entity data multiple times, and/or of there is optional info you store about a client (eg, some long texts, biography, history, extra addresses etc) in which cases it would be optimal to store them on a child-table.
If you find yourself a bunch of columns with all-null values, that means you should strongly consider a child table.
If you only need to try login credentials against the DB table, a stored procedure that returns a bool value depending on if the username/password are correct, will save you the round-trip of the data.
Without indexes the select on the smaller tables will be faster. But you can create the same covering index (id, login, pass) on both tables, so if you need only those 3 columns performance will probably be the same on both tables.
The general question which database structure is better can not be answered without knowing the usage of your database.