I create table with objects to process in SQL Server
The database is in dbserver.
Then, with a my app(c#), I use a SqlDataReader to iterate over all the object, and it makes it in time T. I use multithreading and mutex in my app and it use the same SqlDataReader for all the threads. I run in the serverp1.
Then to make it faster, I separate the object in 2 ranks or groups by a column.
Then I run the myapp in serverp01 for the objects in rank1 (SqlDataReader with a select where rank = 1) and then run the myapp in serverp02 for the object in rank2 (SqlDataReader with a select where rank = 2).
My issue is that it takes the same time T for both configs. May be I'm wrong but it should take T/2 time or close to it.
Somebody has an idea what its happening?
Sounds like you're being bound by IO speed. When you run the thing on serverp1, are the CPU's maxed out? If not, then probably the network or the DB disks are the bottleneck. You can check the disk and network throughput on the DB server to see if they hit certain limit.
If the disk is the bottleneck, them try to make your table rows narrower, each row in your table should be as few bytes a possible. Make sure that the table you're querying only holds the few columns you actually need and that they're as compressed as possible (i.e. highly normalized with integer keys instead of varchar values, non nullable etc).
Remember that even when you only ask for a few columns, the whole page needs to be read from disk into memory. The more rows you can fit onto a page, the less pages the server needs to read.
If the network is the bottleneck, then only selecting the columns you need and making them as narrow (int key instead of varchar value) should be enough.
Regards GJ
Related
This may be a dumb question, but I wanted to be sure. I am creating a Winforms app, and using c# oledbconnection to connect to a MS Access database. Right now, i am using a "SELECT * FROM table_name" and looping through each row to see if it is the row with the criteria I want, then breaking out of the loop if it is. I wonder if the performance would be improved if I used something like "SELECT * FROM table_name WHERE id=something" so basically use a "WHERE" statement instead of looping through every row?
The best way to validate the performance of anything is to test. Otherwise, a lot of assumptions are made about what is the best versus the reality of performance.
With that said, 100% of the time using a WHERE clause will be better than retrieving the data and then filtering via a loop. This is for a few different reasons, but ultimately you are filtering the data on a column before retrieving all of the columns, versus retrieving all of the columns and then filtering out the data. Relational data should be dealt with according to set logic, which is how a WHERE clause works, according to the data set. The loop is not set logic and compares each individual row, expensively, discarding those that don’t meet the criteria.
Don’t take my word for it though. Try it out. Especially try it out when your app has a lot of data in the table.
yes, of course.
if you have a access database file - say shared on a folder. Then you deploy your .net desktop application to each workstation?
And furthermore, say the table has 1 million rows.
If you do this:
SELECT * from tblInvoice WHERE InvoiceNumber = 123245
Then ONLY one row is pulled down the network pipe - and this holds true EVEN if the table has 1 million rows. To traverse and pull 1 million rows is going to take a HUGE amount of time, but if you add criteria to your select, then it would be in this case about 1 million times faster to pull one row as opposed to the whole table.
And say if this is/was multi-user? Then again, even on a network - again ONLY ONE record that meets your criteria will be pulled. The only requirement for this "one row pull" over the network? Access data engine needs to have a useable index on that criteria. Of course by default the PK column (ID) always has that index - so no worries there. But if as per above we are pulling invoice numbers from a table - then having a index on that column (InvoiceNumber) is required for the data engine to only pull one row. If no index can be used - then all rows behind the scenes are pulled until a match occurs - and over a network, then this means significant amounts of data will be pulled without that index across that network (or if local - then pulled from the file on the disk).
I am trying to load 2 huge resultsets(source and target) coming from different RDBMS but the problem with which i am struggling is getting those 2 huge result set in memory.
Considering below are the queries to pull data from source and target:
Sql Server -
select Id as LinkedColumn,CompareColumn from Source order by LinkedColumn
Oracle -
select Id as LinkedColumn,CompareColumn from Target order by LinkedColumn
Records in Source : 12377200
Records in Target : 12266800
Following are the approaches i have tried with some statistics:
1) open data reader approach for reading source and target data:
Total jobs running in parallel = 3
Time taken by Job1 = 01:47:25
Time taken by Job1 = 01:47:25
Time taken by Job1 = 01:48:32
There is no index on Id Column.
Major time is spent here:
var dr = command.ExecuteReader();
Problems:
There are timeout issues also for which i have to kept commandtimeout to 0(infinity) and it is bad.
2) Chunk by chunk reading approach for reading source and target data:
Total jobs = 1
Chunk size : 100000
Time Taken : 02:02:48
There is no index on Id Column.
3) Chunk by chunk reading approach for reading source and target data:
Total jobs = 1
Chunk size : 100000
Time Taken : 00:39:40
Index is present on Id column.
4) open data reader approach for reading source and target data:
Total jobs = 1
Index : Yes
Time: 00:01:43
5) open data reader approach for reading source and target data:
Total jobs running in parallel = 3
Index : Yes
Time: 00:25:12
I observed that while having an index on LinkedColumn does improve performance, the problem is we are dealing with a 3rd party RDBMS table which might not have an index.
We would like to keep database server as free as possible so data reader approach doesn't seem like a good idea because there will be lots of jobs running in parallel which will put so much pressure on database server which we don't want.
Hence we want to fetch records in the resource memory from source to target and do 1 - 1 records comparison to keep the database server free.
Note: I want to do this in my c# application and don't want to use SSIS or Linked Server.
Update:
Source Sql Query Execution time in sql server management studio: 00:01:41
Target Sql Query Execution time in sql server management studio:00:01:40
What will be the best way to read huge result set in memory?
Code:
static void Main(string[] args)
{
// Running 3 jobs in parallel
//Task<string>[] taskArray = { Task<string>.Factory.StartNew(() => Compare()),
//Task<string>.Factory.StartNew(() => Compare()),
//Task<string>.Factory.StartNew(() => Compare())
//};
Compare();//Run single job
Console.ReadKey();
}
public static string Compare()
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
var srcConnection = new SqlConnection("Source Connection String");
srcConnection.Open();
var command1 = new SqlCommand("select Id as LinkedColumn,CompareColumn from Source order by LinkedColumn", srcConnection);
var tgtConnection = new SqlConnection("Target Connection String");
tgtConnection.Open();
var command2 = new SqlCommand("select Id as LinkedColumn,CompareColumn from Target order by LinkedColumn", tgtConnection);
var drA = GetReader(command1);
var drB = GetReader(command2);
stopwatch.Stop();
string a = stopwatch.Elapsed.ToString(#"d\.hh\:mm\:ss");
Console.WriteLine(a);
return a;
}
private static IDataReader GetReader(SqlCommand command)
{
command.CommandTimeout = 0;
return command.ExecuteReader();//Culprit
}
There is nothing (I know of) faster than a DataReader for fetching db records.
Working with large databases comes with its challenges, reading 10 million records in under 2 seconds is pretty good.
If you want faster you can:
jdwend's suggestion:
Use sqlcmd.exe and the Process class to run query and put results into a csv file and then read the csv into c#. sqlcmd.exe is designed to archive large databases and runs 100x faster than the c# interface. Using linq methods are also faster than the SQL Client class
Parallize your queries and fetch concurrently merging results: https://shahanayyub.wordpress.com/2014/03/30/how-to-load-large-dataset-in-datagridview/
The easiest (and IMO the best for a SELECT * all) is to throw hardware at it:
https://blog.codinghorror.com/hardware-is-cheap-programmers-are-expensive/
Also make sure you're testing on the PROD hardware, in release mode as that could skew your benchmarks.
This is a pattern that I use. It gets the data for a particular record set into a System.Data.DataTable instance and then closes and disposes all un-managed resources ASAP. Pattern also works for other providers under System.Data include System.Data.OleDb, System.Data.SqlClient, etc. I believe the Oracle Client SDK implements the same pattern.
// don't forget this using statements
using System.Data;
using System.Data.SqlClient;
// here's the code.
var connectionstring = "YOUR_CONN_STRING";
var table = new DataTable("MyData");
using (var cn = new SqlConnection(connectionstring))
{
cn.Open();
using (var cmd = cn.CreateCommand())
{
cmd.CommandText = "Select [Fields] From [Table] etc etc";
// your SQL statement here.
using (var adapter = new SqlDataAdapter(cmd))
{
adapter.Fill(table);
} // dispose adapter
} // dispose cmd
cn.Close();
} // dispose cn
foreach(DataRow row in table.Rows)
{
// do something with the data set.
}
I think I would deal with this problem in a different way.
But before lets make some assumptions:
According to your question description, you will get data from SQL Server and Oracle
Each query will return a bunch of data
You do not specify what is the point of getting all that data in memory, neither the use of it.
I assume that the data you will process is going to be used multiple times and you will not repeat both queries multiple times.
And whatever you will do with the data, probably is not going to be displayed to the user all at the same time.
Having these foundation points I would process the following:
Think at this problem as a data processing
Have a third database or some other place with auxiliar Database tables where you can store all the result of the 2 queries.
To avoid timeouts or so, try to obtain the data using pagging (get thousands at a time) and save then in these aux DB tables, and NOT in "RAM" memory.
As soon as your logic completes all the data loading (import migration), then you can start processing it.
Data processing is a key point of database engines, they are efficient and lots of evolution during many years, do don't spend time reinventing the wheel. Use some Stored procedure to "crunch/process/merge" of the 2 auxiliary tables into only 1.
Now that you have all "merged" data in a 3th aux table, now you can use it to display or something else you need to use it.
If you want to read it faster, you must use original API to get the data faster. Avoid framework like linq and do rely on DataReader that one. Try to check weather you need something like dirty read (with(nolock) in sql server).
If your data is very huge, try to implement partial read. Something like making index to your data. Maybe you can put condition where date from - to until everything selected.
After that you must consider using Threading in your system to parallelize the flow. Actually 1 thread to get from job 1, another thread to get from job 2. This one will cut lot of time.
Technicalities aside, I think there is a more fundamental problem here.
select [...] order by LinkedColumn
I does observe that while having index on LinkedColumn does improve performance but the problem is we are dealing with 3rd party RDBMS tables which might have index or might not.
We would like to keep database server as free as possible
If you cannot ensure that the DB has a tree based index on that column, it means the DB will be quite busy sorting your millions of elements. It's slow and resource hungry. Get rid of the order by in the SQL statement and perform it on application side to get results faster and reduce load on DB ...or ensure the DB has such an index!!!
...depending if this fetching is a common or a rare operation, you'll want to either enforce a proper index in the DB, or just fetch it all and sort it client side.
I had a similar situation many years ago. Before I looked at the problem it took 5 days running continuously to move data between 2 systems using SQL.
I took a different approach.
We extracted the data from the source system into just a small number of files representing a flattened out data model and arranged the data in each file so it all naturally flowed in the proper sequence as we read from the files.
I then wrote a Java program that processed these flattened data files and produced individual table load files for the target system. So, for example, the source extract had less than a dozen data files from the source system which turned into 30 to 40 or so load files for the target database.
That process would run in just a few minutes and I incorporated full auditing and error reporting and we could quickly spot problems and discrepancies in the source data, get them fixed, and run the processor again.
The final piece of the puzzle was a multi-threaded utility I wrote that performed a parallel bulk load on each load file into the target Oracle database. This utility created a Java process for each table and used Oracle's bulk table load program to quickly push the data into the Oracle DB.
When all was said and done that 5 day SQL-SQL transfer of millions of records turned into just 30 minutes using a combination of Java and Oracle's bulk load capabilities. And there were no errors and we accounted for every penny of every account that was transferred between systems.
So, maybe think outside the SQL box and use Java, the file system, and Oracle's bulk loader. And make sure you're doing your file IO on solid state hard drives.
If you need to process large database result sets from Java, you can opt for JDBC to give you the low level control required. On the other hand, if you are already using an ORM in your application, falling back to JDBC might imply some extra pain. You would be losing features such as optimistic locking, caching, automatic fetching when navigating the domain model and so forth. Fortunately most ORMs, like Hibernate, have some options to help you with that. While these techniques are not new, there are a couple of possibilities to choose from.
A simplified example; let's assume we have a table (mapped to class "DemoEntity") with 100.000 records. Each record consists of a single column (mapped to the property "property" in DemoEntity) holding some random alphanumerical data of about ~2KB. The JVM is ran with -Xmx250m. Let's assume that 250MB is the overall maximum memory that can be assigned to the JVM on our system. Your job is to read all records currently in the table, doing some not further specified processing, and finally store the result. We'll assume that the entities resulting from our bulk operation are not modified
I'm developing an ASP.NET app that analyzes Excel files uploaded by user. The files contain various data about customers (one row = one customer), the key field is CustomerCode. Basically the data comes in form of DataTable object.
At some point I need to get information about the specified customers from SQL and compare it to what user uploaded. I'm doing it the following way:
Make a comma-separated list of customers from CustomerCode column: 'Customer1','Customer2',...'CustomerN'.
Pass this string to SQL query IN (...) clause and execute it.
This was working okay until I ran into The query processor ran out of internal resources and could not produce a query plan exception when trying to pass ~40000 items inside IN (...) clause.
The trivial ways seems to:
Replace IN (...) with = 'SomeCustomerCode' in query template.
Execute this query 40000 times for each CustomerCode.
Do DataTable.Merge 40000 times.
Is there any better way to work this problem around?
Note: I can't do IN (SELECT CustomerCode FROM ... WHERE SomeConditions) because the data comes from Excel files and thus cannot be queried from DB.
"Table valued parameters" would be worth investigating, which let you pass in (usually via a DataTable on the C# side) multiple rows - the downside is that you need to formally declare and name the data shape on the SQL server first.
Alternatively, though: you could use SqlBulkCopy to throw the rows into a staging table, and then just JOIN to that table. If you have parallel callers, you will need some kind of session identifier on the row to distinguish between concurrent uses (and: don't forget to remove your session's data afterwards).
You shouldn't process too many records at once, because of errors as you mentioned, and it is such a big batch that it takes too much time to run and you can't do anything in parallel. You shouldn't process only 1 record at a time either, because then the overhead of the SQL server communication will be too big. Choose something in the middle, process eg. 10000 records at a time. You can even parallelize the processing, you can start running the SQL for the next 10000 in the background while you are processing the previous 10000 batch.
hi guys i have this doubt ...
if i have a record of username and password details for logging in to a website I'll most probably get the user name and password from the form and will be using to check if the given username is present in the database by using a contains() Boolean operation and if contains then check the password is same as saved in the database..
but for websites like g-mail and Facebook there are million of records and the authentication is very quick ...
how to they do it ..what method do they follow for this
how they check if a value is present in a large record that quickly ?
does the process involve just adding more server for processing speed ?
ty for the answers ...
**
sorry i have posted this question without knowing about indexers ..
(just came to know that by creating indexes to one or multiple column
the full table scan is minimized and index path is used instead which
is less costlier and more efficient operation ..)
**
You just need one SQL query:
select 1 from user u
where u.login = :theEnteredLogin
and u.hashed_password = :theHashedEnteredPassword
(where :xxx are parameters of the query).
If you have an index on the login column or even better, on [login - hashed_password], the query should not take more than a few milliseconds to execute.
Well, they have lots of servers and high-performance databases. At a low level, the table for the hash is probably indexed by the hash for fast lookup - binary search style.
For medium to large data sets indexing, combined with proper sizing of disk, memory and cpus, is the most adopted approach.
For very large data sets, the database can be distributed and data partitioned.
For very, very large data sets, aside from the above scenarios, used technologies usually involve using map reduce model.
Nightly, I need to fill a SQL Server 2005 table from an ODBC source with over 8 million records. Currently I am using an insert statement from linked server with syntax select similar to this:
Insert Into SQLStagingTable from Select * from OpenQuery(ODBCSource, 'Select * from SourceTable')
This is really inefficient and takes hours to run. I'm in the middle of coding a solution using SqlBulkInsert code similar to the code found in this question.
The code in that question is first populating a datatable in memory and then passing that datatable to the SqlBulkInserts WriteToServer method.
What should I do if the populated datatable uses more memory than is available on the machine it is running (a server with 16GB of memory in my case)?
I've thought about using the overloaded ODBCDataAdapter fill method which allows you to fill only the records from x to n (where x is the start index and n is the number of records to fill). However that could turn out to be an even slower solution than what I currently have since it would mean re-running the select statement on the source a number of times.
What should I do? Just populate the whole thing at once and let the OS manage the memory? Should I populate it in chunks? Is there another solution I haven't thought of?
The easiest way would be to use ExecuteReader() against your odbc data source and pass the IDataReader to the WriteToServer(IDataReader) overload.
Most data reader implementations will only keep a very small portion of the total results in memory.
SSIS performs well and is very tweakable. In my experience 8 million rows is not out of its league. One of my larger ETLs pulls in 24 million rows a day and does major conversions and dimensional data warehouse manipulations.
If you have indexes on the destination table, you might consider disabling those till the records get inserted?