TStringList of objects taking up tons of memory in Delphi XE - delphi

I'm working on a simulation program.
One of the first things the program does is read in a huge file (28 mb, about 79'000 lines,), parse each line (about 150 fields), create a class for the object, and add it to a TStringList.
It also reads in another file, which adds more objects during the run. At the end, it ends up being about 85'000 objects.
I was working with Delphi 2007, and the program used a lot of memory, but it ran OK. I upgraded to Delphi XE, and migrated the program over and now it's using a LOT more memory, and it ends up running out of memory half way through the run.
So in Delphi 2007, it would end up using 1.4 gigs after reading in the initial file, which is obviously a huge amount, but in XE, it ends up using almost 1.8 gigs, which is really huge and leads to running out and getting the error
So my question is
Why is it using so much memory?
Why is it using so much more memory in XE than 2007?
What can I do about this? I can't change how big or long the file is, and I do need to create an object for each line and to store it somewhere
Thanks

Just one idea which may save memory.
You could let the data stay on the original files, then just point to them from in-memory structures.
For instance, it's what we do for browsing big log files almost instantly: we memory-map the log file content, then we parse it quick to create indexes of useful information in memory, then we read the content dynamically. No string is created during the reading. Only pointers to each line beginning, with dynamic arrays containing the needed indexes. Calling TStringList.LoadFromFile would be definitively much slower and memory consuming.
The code is here - see the TSynLogFile class. The trick is to read the file only once, and make all indexes on the fly.
For instance, here is how we retrieve a line of text from the UTF-8 file content:
function TMemoryMapText.GetString(aIndex: integer): string;
begin
if (self=nil) or (cardinal(aIndex)>=cardinal(fCount)) then
result := '' else
result := UTF8DecodeToString(fLines[aIndex],GetLineSize(fLines[aIndex],fMapEnd));
end;
We use the exact same trick to parse JSON content. Using such a mixed approach is used by the fastest XML access libraries.
To handle your high-level data, and query them fast, you may try to use dynamic arrays of records, and our optimized TDynArray and TDynArrayHashed wrappers (in the same unit). Arrays of records will be less memory consuming, will be faster to search in because the data won't be fragemented (even faster if you use ordered indexes or hashes), and you'll be able to have high-level access to the content (you can define custom functions to retrieve the data from the memory mapped file, for instance). Dynamic arrays won't fit fast deletion of items (or you'll have to use lookup tables) - but you wrote you are not deleting much data, so it won't be a problem in your case.
So you won't have any duplicated structure any more, only logic in RAM, and data on memory-mapped file(s) - I added a "s" here because the same logic could perfectly map to several source data files (you need some "merge" and "live refresh" AFAIK).

It's hard to say why your 28 MB file is expanding to 1.4 GB worth of objects when you parse it out into objects without seeing the code and the class declarations. Also, you say you're storing it in a TStringList instead of a TList or TObjecList. This sounds like you're using it as some sort of string->object key/value mapping. If so, you might want to look at the TDictionary class in the Generics.Collections unit in XE.
As for why you're using more memory in XE, it's because the string type changed from an ANSI string to a UTF-16 string in Delphi 2009. If you don't need Unicode, you could use a TDictionary to save space.
Also, to save even more memory, there's another trick you could use if you don't need all 79,000 of the objects right away: lazy loading. The idea goes something like this:
Read the file into a TStringList. (This will use about as much memory as the file size. Maybe twice as much if it gets converted into Unicode strings.) Don't create any data objects.
When you need a specific data object, call a routine that checks the string list and looks up the string key for that object.
Check if that string has an object associated with it. If not, create the object from the string and associate it with the string in the TStringList.
Return the object associated with the string.
This will keep both your memory usage and your load time down, but it's only helpful if you don't need all (or a large percentage) of the objects immediately after loading.

In Delphi 2007 (and earlier), a string is an Ansi string, that is, every character occupies 1 byte of memory.
In Delphi 2009 (and later), a string is a Unicode string, that is, every character occupies 2 bytes of memory.
AFAIK, there is no way to make a Delphi 2009+ TStringList object use Ansi strings. Are you really using any of the features of the TStringList? If not, you could use an array of strings instead.
Then, naturally, you can choose between
type
TAnsiStringArray = array of AnsiString;
// or
TUnicodeStringArray = array of string; // In Delphi 2009+,
// string = UnicodeString

Reading though the comments, it sounds like you need to lift the data out of Delphi and into a database.
From there it is easy to match organ donors to receivers*)
SELECT pw.* FROM patients_waiting pw
INNER JOIN organs_available oa ON (pw.bloodtype = oa.bloodtype)
AND (pw.tissuetype = oa.tissuetype)
AND (pw.organ_needed = oa.organ_offered)
WHERE oa.id = '15484'
If you want to see the patients that might match against new organ-donor 15484.
In memory you only handle the few patients that match.
*) simplified beyond all recognition, but still.

In addition to Andreas' post:
Before Delphi 2009, a string header occupied 8 bytes. Starting with Delphi 2009, a string header takes 12 bytes. So every unique string uses 4 bytes more than before, + the fact that each character takes twice the memory.
Also, starting with Delphi 2010 I believe, TObject started using 8 bytes instead of 4. So for each single object created by delphi, delphi now uses 4 more bytes. Those 4 bytes were added to support the TMonitor class I believe.
If you're in desperate need to save memory, here's a little trick that could help if you have a lot of string value that repeats themselve.
var
uUniqueStrings : TStringList;
function ReduceStringMemory(const S : String) : string;
var idx : Integer;
begin
if not uUniqueStrings.Find(S, idx) then
idx := uUniqueStrings.Add(S);
Result := uUniqueStrings[idx]
end;
Note that this will help ONLY if you have a lot of string values that repeat themselves. For exemple, this code use 150mb less on my system.
var sl : TStringList;
I: Integer;
begin
sl := TStringList.Create;
try
for I := 0 to 5000000 do
sl.Add(ReduceStringMemory(StringOfChar('A',5)));every
finally
sl.Free;
end;
end;

I also read in a lot of strings in my program that can approach a couple of GB for large files.
Short of waiting for 64-bit XE2, here is one idea that might help you:
I found storing individual strings in a stringlist to be slow and wasteful in terms of memory. I ended up blocking the strings together. My input file has logical records, which may contain between 5 and 100 lines. So instead of storing each line in the stringlist, I store each record. Processing a record to find the line I need adds very little time to my processing, so this is possible for me.
If you don't have logical records, you might just want to pick a blocking size, and store every (say) 10 or 100 strings together as one string (with a delimiter separating them).
The other alternative, is to store them in a fast and efficient on-disk file. The one I'd recommend is the open source Synopse Big Table by Arnaud Bouchez.

May I suggest you try using the jedi class library (JCL) class TAnsiStringList, which is like TStringList fromDelphi 2007 in that it is made up of AnsiStrings.
Even then, as others have mentioned, XE will be using more memory than delphi 2007.
I really don't see the value of loading the full text of a giant flat file into a stringlist. Others have suggested a bigtable approach such as Arnaud Bouchez's one, or using SqLite, or something like that, and I agree with them.
I think you could also write a simple class that will load the entire file you have into memory, and provide a way to add line-by-line object links to a giant in-memory ansichar buffer.

Starting with Delphi 2009, not only strings but also every TObject has doubled in size. (See Why Has the Size of TObject Doubled In Delphi 2009?). But this would not explain this increase if there are only 85,000 objects. Only if these objects contain many nested objects, their size could be a relevant part of the memory usage.

Are there many duplicate strings in your list? Maybe trying to only store unique strings will help reducing the memory size. See my Question
about a string pool for a possible (but maybe too simple) answer.

Are you sure you don't suffer from a case of memory fragementation?
Be sure to use the latest FastMM (currently 4.97), then take a look at the UsageTrackerDemo demo that contains a memory map form showing the actual usage of the Delphi memory.
Finally take a look at VMMap that shows you how your process memory is used.

Related

Difference between Record and Packed Record [duplicate]

While reviewing some code in our legacy Delphi 7 program, I noticed that everywhere there is a record it is marked with packed. This of course means that the record is stored byte-for-byte and not aligned to be faster for the CPU to access. The packing seems to have been done blindly as an attempt to outsmart the compiler or something -- basically valuing a few bytes of memory instead of faster access
An example record:
TFooTypeRec = packed record
RID : Integer;
Description : String;
CalcInTotalIncome : Boolean;
RequireAddress : Boolean;
end;
Should I fix this and make every record normal or "not" packed? Or with modern CPUs and memory is this negligible and probably a waste of time? Are there any problems that can result from unpacking?
There is no way to answer this question without a full understanding of how each of those packed records are used in your application code. It is the same as asking "Should I change this variable declaration from Int64 to Byte ?"
Without knowing what values that variable will be expected and required to maintain the answer could be yes. Or it could be no.
Similarly in your case. If a record needs to be packed then it should be left packed. If it does not need to be packed then there is no harm in not packing it. If you are not sure or cannot tell, then the safest course is to leave them as they are.
As a guide to making this determination (should you decide to proceed), situations where record packing is required or recommended include:
persistence of record values
sharing of record values with [potentially] differently compiled code
strict compatibility with externally defined structures
deliberately overlaying a type layout over differently structured memory
This isn't necessarily an exhaustive list, and what these all have in common is:
records comprising a series of values in adjacent bytes that must and can be relied upon by any potential producer or consumer of the record without possibility of interference from the compiler or other factors
What I would recommend is that (if possible and practical) you determine what purpose packing serves in each case and add documentation to that effect to the record declaration itself so that anyone in the future with the same question doesn't have to go through that discovery process, e.g.:
type
TSomeRecordType = packed record
// This record must be packed as it is used for persistence
..
end;
TSomeExternType = packed record
// This record must be packed as it is required to be compatible
// in memory with an externally defined struct (ref: extern code docs)
..
end;
The main idea of using packed records is not that you save a few bytes of memory! Instead, it is about guaranteeing that the variables are where you expect them to be in memory. Without such a guarantee, it would be impossible (or, at least, difficult) to manage memory manually on the heap and write to and read from files.
Hence, the program might malfunction if you 'unpack' the records!
If the record is stored/retrieved as packed or transfered in any way to a receiver that expects it to be packed, then do not change it.
Update :
There is a string type declared in your example. It looks suspicious, since storing the record in a binary file will not preserve the string content.
Packed record have length exactly size like members are.
No packed record are optimised (thay are aligned -> consequently higher) for better performance.

What is the fastest mean to transfer a record in DCOM

I want to transfer some records with the following structure between two Windows PC computer using COM/DCOM. I prefer to transfer an array, say 100 members of TARec, at a time, not each record individually. Currently I am doing this using IStrings. I am looking to improve it using the raw records, to save the time to encode/decode the strings at both ends. Please share your experience.
type
TARec = record
A : TDateTime;
B : WORD;
C : Boolean;
D : Double;
end;
All the record's field type are OLE compatible. Many thanks in advance.
As Rudy suggests in the comments, if your data contains simple value types then a variant byte array can be a very efficient approach and quite simple to implement.
Since you have stated that your data already resides in an array, the basic approach would be:
Create a byte array of the required size to hold all your record data (use VarArrayCreate with type varByte)
Lock the array to obtain a pointer that is safe to use to reference the array contents in memory (VarArrayLock will lock and return a pointer to the array data)
Use CopyMemory to directly copy the data from your array of records to the byte array memory.
Unlock the variant array (VarArrayUnlock) and pass it through your COM/DCOM interface
On the other ('receiving') side you simply reverse the process:
Declare an array of records of the required size
Lock the variant byte array to obtain a pointer to the memory holding the bytes
Copy the byte array data into your record array
Unlock the byte array
This exact approach is something I have used very successfully in a very demanding COM/DCOM scenario (w.r.t efficiency/performance) in the past.
Things to be careful of:
If your data ever changes to include more complex types such as strings or dynamic arrays then additional work will be required to correctly transport these through a byte array.
If your data structure ever changes then the code on both sides of the interface will need to be updated accordingly. One way to protect against this is to incorporate some mechanism for the data to be identified as valid or not by the receiver. This could include a "version number" for example and/or a value (in a 'header' as part of the byte array, in addition to the array data, or passed as a separate parameter entirely - precise details don't really matter). If the receiver finds a version number or size that it is not expecting then it can report this gracefully rather than naively processing the data incorrectly and (most likely) crashing or throwing exceptions as a result.
Alignment/packing issues. Even with the same declaration for the record type, if code is compiled with different alignment settings then the size required for each record in memory could change (which is why a "version number" for the data structure format might not be reliable on its own). One way to avoid this would be to declare the record as packed, though this comes at the cost of a slight reduction in efficiency (and still relies on both sides of the interface agreeing that the data structure is packed).
There are just things to bear in mind however, not prescriptive. Just how complex/robust your implementation needs to be will be determined by your specific case.

TClientDataSet and limit by memory

We have a system that creates reports out of our data. And we can deal with a lot of data. The idea of over 150,000 rows is not out of the question.
Unfortunately, our experience with TClientDataSet is its limitations, because it often results in an 'insufficient memory for this operation' error, when the data gets too big.
So the question is this: Does there exist a generally available implementation of TDataSet that can handle a large amount of data (such as streaming directly to a file and not keeping the entire dataset in memory)?
I am willing to implement such a class myself. But as far as I understand TClientDataSet, it needs to be able to contain the data itself before it can save it to a file/stream. In addition, loading the data again should also be possible as a stream rather than loading in an entire TClientDataSet object, because then we wouldn't have solved the issue.
You can use either FireBird or Interbase in embedded mode.
Is there really any need to cache all the data on the client before reporting? If not, maybe rethink how you're querying and processing data to generate these reports and see if there's a way that involves less client-side data (which comes with a bonus of less data transmitted over the network).
If you've been down that road before and you really do need all this data client side, then you could look at custom data structures. A TList<T> of records (even if you need to build your own indexes) takes a lot less memory than a TClientDataSet does.
KBMMemTable is a nice alternative to TClientDataset
http://www.components4programmers.com/products/kbmmemtable/
We are using it for years and it is very useful and fast.
Wanted to underline that the capacities of the TClientDataset could be something bigger.
Test on the limits of TClientDataset - appending xxx,xxx records, putting the single record in whole (repeated) to create an idea on the size.
// Begin Load Record to TCLientDataset for Reverse (on Reverse) Processing
dxMemData1.Append;
dxMemData1['NT_Rec_No'] := 1000;
dxMemData1['NT_User'] := 'DEV\Administrator';
dxMemData1['NT_Type'] := 'Information';
dxMemData1['Ora_Timestamp'] := '20170706033859.000';
dxMemData1['Ora_Host'] := 'DEV0001';
dxMemData1['Ora_SID'] := 'Oracle.orcl';
dxMemData1['Ora_Event_Id'] := '34';
dxMemData1['NT_Message'] := Memo1.Text;
dxMemData1.Post;
// End Load Record to TCLientDataset for Reverse (on Reverse) Processing
String on the memo1 is a of 100 characters - ansi
did several tests and managed to keep going to something from 600,000 to 900,000 records without crashing.
Difference can be made by making the text on the memo bigger - this did decrease the max number before crash - which means it is not a matter of exact max. record number - but of size consumed - my guess.
Tested the same with TdxMemData (devexpress), this time I could reach almost the double of records

String to Byte [delphi]

I need to store my data into memory. My type data of my data is string. I want to minimize the memory usage. I guess I have to change string into byte. Am I right? If I convert string to byte, that means I have to convert string to TMemoryStream?
If you really want to convert it then this code will get it done
var
BinarySize: Integer;
InputString: string;
StringAsBytes: array of Byte;
begin
BinarySize := (Length(InputString) + 1) * SizeOf(Char);
SetLength(StringAsBytes, BinarySize);
Move(InputString[1], StringAsBytes[0], BinarySize);
But as already stated this will not save you memory. The ammount of it used will be practically the same. You will gain nothing from this alone. If you are having to many strings take a different approach. Like something from this list of choices:
Use a dictionary and only store each same string once
Only hold a portion of all strings in memory. Some sort of cache. Have others on hard drive and use streams to load them
If you have very large string consider compressing them.
If you are reading from file and you target is binary data, skip the string in the middle. Read the source directly into a byte buffer.
It is hard to give further help without knowing more about the problem.
EDIT:
If you really want a minimum memory footprint and you can live with a little lower speed (but still very fast) you can use Suffix Trie or B-Tree or event a simple Binary Tree. They can work directly from hard drive and can be very fast for searching. If you then cache a subset of the data to RAM, you get the optimal solution memory vs. speed wise.
Anyway given the ammount of data you claim to have it seems no memory optimization is needed at all. 22MB of RAM is hardly an issue and not worth optimizing.
Are you certain this is an optimization that is needed?
2000 lines that are 10 characters long is only 20000 characters.
In most environments, that's tiny. Most machines have considerably more RAM than that. Most disks are considerably larger than that. And, usually, sending and receiving that much information is trivial over the web.
Perhaps your situation is unique. Maybe you have large number of 20000 character data sets, or very slow web access over which to transmit this date, etc. But, I'd encourage you to consider whether you aren't perhaps trying to optimize something that even if you are very successful in implementing, won't significantly change your application's performance in the real world.
Make your storage type tutf8string. It can be simply assigned from tunicodestring, and conversion should be safe.

How to handle billions of objects without "Outofmemory" error

I have an application which may needs to process billions of objects.Each object of is of TRange class type. These ranges are created at different parts of an algorithm which depends on certain conditions and other object properties. As a result, if you have 100 items, you can't directly create the 100th object without creating all the prior objects. If I create all the (billions of) objects and add to the collection, the system will throw Outofmemory error. Now I want to iterate through each object mainly for two purposes:
To apply an operation for each TRange object(eg:Output certain properties)
To get a cumulative sum of a certain property.(eg: Each range has a weight property and I want to retreive totalweight that is a sum of all the range weights).
How do I effectively create an Iterator for these object without raising Outofmemory?
I have handled the first case by passing a function pointer to the algorithm function. For eg:
procedure createRanges(aProc: TRangeProc);//aProc is a pointer to function that takes a //TRange
var range: TRange;
rangerec: TRangeRec;
begin
range:=TRange.Create;
try
while canCreateRange do begin//certain conditions needed to create a range
rangerec := ReturnRangeRec;
range.Update(rangerec);//don't create new, use the same object.
if Assigned(aProc) then aProc(range);
end;
finally
range.Free;
end;
end;
But the problem with this approach is that to add a new functionality, say to retrieve the Total weight I have mentioned earlier, either I have to duplicate the algorithm function or pass an optional out parameter. Please suggest some ideas.
Thank you all in advance
Pradeep
For such large ammounts of data you need to only have a portion of the data in memory. The other data should be serialized to the hard drive. I tackled such a problem like this:
I Created an extended storage that can store a custom record either in memory or on the hard drive. This storage has a maximum number of records that can live simultaniously in memory.
Then I Derived the record classes out of the custom record class. These classes know how to store and load themselves from the hard drive (I use streams).
Everytime you need a new or already existing record you ask the extended storage for such a record. If the maximum number of objects is exceeded, the storage streams some of the least used record back to the hard drive.
This way the records are transparent. You always access them as if they are in memory, but they may get loaded from hard drive first. It works really well. By the way RAM works in a very similar way so it only holds a certain subset of all you data on your hard drive. This is your working set then.
I did not post any code because it is beyond the scope of the question itself and would only confuse.
Look at TgsStream64. This class can handle a huge amounts of data through file mapping.
http://code.google.com/p/gedemin/source/browse/trunk/Gedemin/Common/gsMMFStream.pas
But the problem with this approach is that to add a new functionality, say to retrieve the Total weight I have mentioned earlier, either I have to duplicate the algorithm function or pass an optional out parameter.
It's usually done like this: you write a enumerator function (like you did) which receives a callback function pointer (you did that too) and an untyped pointer ("Data: pointer"). You define a callback function to have first parameter be the same untyped pointer:
TRangeProc = procedure(Data: pointer; range: TRange);
procedure enumRanges(aProc: TRangeProc; Data: pointer);
begin
{for each range}
aProc(range, Data);
end;
Then if you want to, say, sum all ranges, you do it like this:
TSumRecord = record
Sum: int64;
end;
PSumRecord = ^TSumRecord;
procedure SumProc(SumRecord: PSumRecord; range: TRange);
begin
SumRecord.Sum := SumRecord.Sum + range.Value;
end;
function SumRanges(): int64;
var SumRec: TSumRecord;
begin
SumRec.Sum := 0;
enumRanges(TRangeProc(SumProc), #SumRec);
Result := SumRec.Sum;
end;
Anyway, if you need to create billions of ANYTHING you're probably doing it wrong (unless you're a scientist, modelling something extremely large scale and detailed). Even more so if you need to create billions of stuff every time you want one of those. This is never good. Try to think of alternative solutions.
"Runner" has a good answer how to handle this!
But I would like to known if you could do a quick fix: make smaller TRange objects.
Maybe you have a big ancestor? Can you take a look at the instance size of TRange object?
Maybe you better use packed records?
This part:
As a result, if you have 100 items,
you can't directly create the 100th
object without creating all the prior
objects.
sounds a bit like calculating Fibonacci. May be you can reuse some of the TRange objects instead of creating redundant copies? Here is a C++ article describing this approach - it works by storing already calculated intermediate results in a hash map.
Handling billions of objects is possible but you should avoid it as much as possible. Do this only if you absolutely have to...
I did create a system once that needed to be able to handle a huge amount of data. To do so, I made my objects "streamable" so I could read/write them to disk. A larger class around it was used to decide when an object would be saved to disk and thus removed from memory. Basically, when I would call an object, this class would check if it's loaded or not. If not, it would re-create the object again from disk, put it on top of a stack and then move/write the bottom object from this stack to disk. As a result, my stack had a fixed (maximum) size. And it allowed me to use an unlimited amount of objects, with a reasonable good performance too.
Unfortunately, I don't have that code available anymore. I wrote it for a previous employer about 7 years ago. I do know that you would need to write a bit of code for the streaming support plus a bunch more for the stack controller which maintains all those objects. But it technically would allow you to create an unlimited number of objects, since you're trading RAM memory for disk space.

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