We Keep Coding

What is the best way to load huge result set in memory?

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

Performance Tuning: Saving records exponentially grows every 500 records?

I wrote a class to read in a CSV file that houses 4k records, 72 col wide. The 'read()' into the List takes literally a second, maybe...
Once I have successfully loaded up the List, I have the general flow for saving each object to the db;
foreach (var object in Objects)
{
try{
// check conditions
// perform conversions on the data and assign to domain object.property
//....
//db.object.Add(object);
//db.savechanges();
}catch{
//update log if the try fails
}
}
Once the loop executes successfully, I call db.dispose();
I haven't built too many classes outside of the MVC controller structure because I'm new to this so go easy on me ;). I'm assuming that I'm tying up precious resources using this approach which is causing the exponential processing time issue.
Any suggestions on how to improve performance? Thanks in advance!

If you're working with SQL Server and willing to use something outside of Entity-framework there's a bulk copy routine that might be very useful for you. Basically what you do is to create a table in memory (its a .net object) and then add your records to that. Once you've added all 72K records to the table then you'll all at once save that to the database. Since this uses bulk copy functionality that's tuned for this scenario its extremely fast.
Here's a couple articles that might get you started:
http://www.codeproject.com/Articles/16922/SQL-Bulk-Copy-with-C-Net
http://www.codeproject.com/Articles/18418/Transferring-Data-Using-SqlBulkCopy
http://dotnetmentors.com/c-sharp/bulk-upload-into-sql-server-using-sqlbulkcopy-and-c-sharp.aspx

This credit should really go to Atoms for pointing out the "AutoDetectChangesEnabled" reference. I found a great article by Rick Strahl here; http://weblog.west-wind.com/posts/2013/Dec/22/Entity-Framework-and-slow-bulk-INSERTs which explains it well!
My 15 min processing just got knocked down to 45 seconds wooot!!!
Thanks!

'Streaming' data into Sql server

I'm working on a project where we're receiving data from multiple sources, that needs to be saved into various tables in our database.
Fast.
I've played with various methods, and the fastest I've found so far is using a collection of TableValue parameters, filling them up and periodically sending them to the database via a corresponding collection of stored procedures.
The results are quite satisfying. However, looking at disk usage (% Idle Time in Perfmon), I can see that the disk is getting periodically 'thrashed' (a 'spike' down to 0% every 13-18 seconds), whilst in between the %Idle time is around 90%. I've tried varying the 'batch' size, but it doesn't have an enormous influence.
Should I be able to get better throughput by (somehow) avoiding the spikes while decreasing the overall idle time?
What are some things I should be looking out to work out where the spiking is happening? (The database is in Simple recovery mode, and pre-sized to 'big', so it's not the log file growing)
Bonus: I've seen other questions referring to 'streaming' data into the database, but this seems to involve having a Stream from another database (last section here). Is there any way I could shoe-horn 'pushed' data into that?

A very easy way of inserting loads of data into an SQL-Server is -as mentioned- the 'bulk insert' method. ADO.NET offers a very easy way of doing this without the need of external files. Here's the code
var bulkCopy = new SqlBulkCopy(myConnection);
bulkCopy.DestinationTableName = "MyTable";
bulkCopy.WriteToServer (myDataSet);
That's easy.
But: myDataSet needs to have exactly the same structure as MyTable, i.e. Names, field types and order of fields must be exactly the same. If not, well there's a solution to that. It's column mapping. And this is even easier to do:
bulkCopy.ColumnMappings.Add("ColumnNameOfDataSet", "ColumnNameOfTable");
That's still easy.
But: myDataSet needs to fit into memory. If not, things become a bit more tricky as we have need a IDataReader derivate which allows us to instantiate it with an IEnumerable.
You might get all the information you need in this article.

Building on the code referred to in alzaimar's answer, I've got a proof of concept working with IObservable (just to see if I can). It seems to work ok. I just need to put together some tidier code to see if this is actually any faster than what I already have.
(The following code only really makes sense in the context of the test program in code download in the aforementioned article.)
Warning: NSFW, copy/paste at your peril!
private static void InsertDataUsingObservableBulkCopy(IEnumerable<Person> people,
SqlConnection connection)
{
var sub = new Subject<Person>();
var bulkCopy = new SqlBulkCopy(connection);
bulkCopy.DestinationTableName = "Person";
bulkCopy.ColumnMappings.Add("Name", "Name");
bulkCopy.ColumnMappings.Add("DateOfBirth", "DateOfBirth");
using(var dataReader = new ObjectDataReader<Person>(people))
{
var task = Task.Factory.StartNew(() =>
{
bulkCopy.WriteToServer(dataReader);
});
var stopwatch = Stopwatch.StartNew();
foreach(var person in people) sub.OnNext(person);
sub.OnCompleted();
task.Wait();
Console.WriteLine("Observable Bulk copy: {0}ms",
stopwatch.ElapsedMilliseconds);
}
}

It's difficult to comment without knowing the specifics, but one of the fastest ways to get data into SQL Server is Bulk Insert from a file.
You could write the incoming data to a temp file and periodically bulk insert it.
Streaming data into SQL Server Table-Valued parameter also looks like a good solution for fast inserts as they are held in memory. In answer to your question, yes you could use this, you just need to turn your data into a IDataReader. There's various ways to do this, from a DataTable for example see here.
If your disk is a bottleneck you could always optimise your infrastructure. Put database on a RAM disk or SSD for example.

Microsoft SQL Server insert data into large table at every second

I have a data acquisition system that reads values from some industrial devices and records values into Microsoft SQL Server 2008 R2 database. Data record interval is approximately 20 seconds. Every record data contains approximately 600 bytes of data.
Now I need to insert data from a new hardware but this time record interval has to be 1 second. In other words I insert 1 record of 600 bytes into SQL server database in every second.
I have two questions:
Is there any possible problem that I may run into while inserting data in every second? I think Microsoft SQL server is quite OK for this frequency of insertion but I am not sure for a long-period.
Program is a long running application. I clear the data table approximately every week. When I record data in every second I will have 3600 rows in the table every hour and 86400 rows every day and approximately 600K rows at the end of week. Is this OK for a good level of reading data? Or should I try to change my approach in order not to have such amount of rows in the table?
By the way I use LinqToSQL for all my database operations and C# for programming.

Is there any possible problem that I may run into while inserting data in every second? I think Microsoft SQL server is quite OK for this frequency of insertion but I am not sure for a long-period.
If database is properly designed than you should not run into any problem. We save GIS data at much greater speed without any issue.
Is this OK for a good level of reading data? Or should I try to change my approach in order not to have such amount of rows in the table?
It depends, if you need all the data than how can you change the approach? if you don't need it why do you save it?

First of all, you must think about existing indexes on tables in which you insert data, because indexes slowing down insert process. Second, if you have FULL recovery model, then every insert process will be written in transaction log, and your log file will rapidly rise.
Think about change your recovery model to SIMPLE, and to disable your indexes.
Of course, selecting rows from that table will be slower, but I don't know what is your requests.

Based on my thesis experience in college, if your system is fully stable and doesn't crash or overflow or etc. You can use SqlBulkCopy to avoid I/O operation per record.
This is sample code of bulk copy for DataTable and this method should call every 1 hour:
private void SaveNewData()
{
if (cmdThesis.Connection.State == ConnectionState.Open)
{
cmdThesis.Connection.Close();
}
SqlBulkCopy bulkCopy = new SqlBulkCopy(#"Data Source=.;Initial Catalog=YourDb;Integrated Security=True");
bulkCopy.BatchSize = 3000;
bulkCopy.ColumnMappings.Add(new SqlBulkCopyColumnMapping("Col1", "Col1"));
bulkCopy.ColumnMappings.Add(new SqlBulkCopyColumnMapping("Col2", "Col2"));
bulkCopy.ColumnMappings.Add(new SqlBulkCopyColumnMapping("Col3", "Col3"));
bulkCopy.ColumnMappings.Add(new SqlBulkCopyColumnMapping("Col4", "Col4"));
bulkCopy.DestinationTableName = "DestinationTable";
bulkCopy.WriteToServer(Result);
Result.Rows.Clear();
}

Although I think you should be ok, since you are apparently using a .NET platform, you can check out StreamInsight: http://technet.microsoft.com/en-us/library/ee391416.aspx

SQL - Better two queries instead of one big one

I am working on a C# application, which loads data from a MS SQL 2008 or 2008 R2 database. The table looks something like this:
ID | binary_data | Timestamp
I need to get only the last entry and only the binary data. Entries to this table are added irregular from another program, so I have no way of knowing if there is a new entry.
Which version is better (performance etc.) and why?
//Always a query, which might not be needed
public void ProcessData()
{
byte[] data = "query code get latest binary data from db"
}
vs
//Always a smaller check-query, and sometimes two queries
public void ProcessData()
{
DateTime timestapm = "query code get latest timestamp from db"
if(timestamp > old_timestamp)
data = "query code get latest binary data from db"
}
The binary_data field size will be around 30kB. The function "ProcessData" will be called several times per minutes, but sometimes can be called every 1-2 seconds. This is only a small part of a bigger program with lots of threading/database access, so I want to the "lightest" solution. Thanks.

Luckily, you can have both:
SELECT TOP 1 binary_data
FROM myTable
WHERE Timestamp > #last_timestamp
ORDER BY Timestamp DESC
If there is a no record newer than #last_timestamp, no record will be returned and, thus, no data transmission takes place (= fast). If there are new records, the binary data of the newest is returned immediately (= no need for a second query).

I would suggest you perform tests using both methods as the answer would depend on your usages. Simulate some expected behaviour.
I would say though, that you are probably okay to just do the first query. Do what works. Don't prematurely optimise, if the single query is too slow, try your second two-query approach.

Two-step approach is more efficient from overall workload of system point of view:
Get informed that you need to query new data
Query new data
There are several ways to implement this approach. Here are a pair of them.
Using Query Notifications which is built-in functionality of SQL Server supported in .NET.
Using implied method of getting informed of database table update, e.g. one described in this article at SQL Authority blog

I think that the better path is a storedprocedure that keeps the logic inside the database, Something with an output parameter with the data required and a return value like a TRUE/FALSE to signal the presence of new data