Develop Reference

EF - A proper way to search several items in database

I have about 100 items (allRights) in the database and about 10 id-s to be searched (inputRightsIds). Which one is better - first to get all rights and then search the items (Variant 1) or to make 10 checking requests requests to the database
Here is some example code:
DbContext db = new DbContext();
int[] inputRightsIds = new int[10]{...};
Variant 1
var allRights = db.Rights.ToLIst();
foreach( var right in allRights)
{
for(int i>0; i<inputRightsIds.Lenght; i++)
{
if(inputRightsIds[i] == right.Id)
{
// Do something
}
}
}
Variant 2
for(int i>0; i<inputRightsIds.Lenght; i++)
{
if(db.Rights.Any(r => r.Id == inputRightsIds[i]);)
{
// Do something
}
}
Thanks in advance!

As other's have already stated you should do the following.
var matchingIds = from r in db.Rights
where inputRightIds.Contains(r.Id)
select r.Id;
foreach(var id in matchingIds)
{
// Do something
}
But this is different from both of your approaches. In your first approach you are making one SQL call to the DB that is returning more results than you are interested in. The second is making multiple SQL calls returning part of the information you want with each call. The query above will make one SQL call to the DB and return only the data you are interested in. This is the best approach as it reduces the two bottle necks of making multiple calls to the DB and having too much data returned.

You can use following :
db.Rights.Where(right => inputRightsIds.Contains(right.Id));

They should be very similar speeds since both must enumerate the arrays the same number of times. There might be subtle differences in speed between the two depending on the input data but in general I would go with Variant 2. I think you should almost always prefer LINQ over manual enumeration when possible. Also consider using the following LINQ statement to simplify the whole search to a single line.
var matches = db.Rights.Where(r=> inputRightIds.Contains(r.Id));
...//Do stuff with matches

Not forget get all your items into memory to process list further
var itemsFromDatabase = db.Rights.Where(r => inputRightsIds.Contains(r.Id)).ToList();
Or you could even enumerate through collection and do some stuff on each item
db.Rights.Where(r => inputRightsIds.Contains(r.Id)).ToList().Foreach(item => {
//your code here
});

A better way to loop through lists

So I have a couple of different lists that I'm trying to process and merge into 1 list.
Below is a snipet of code that I want to see if there was a better way of doing.
The reason why I'm asking is that some of these lists are rather large. I want to see if there is a more efficient way of doing this.
As you can see I'm looping through a list, and the first thing I'm doing is to check to see if the CompanyId exists in the list. If it does, then I find item in the list that I'm going to process.
pList is my processign list. I'm adding the values from my different lists into this list.
I'm wondering if there is a "better way" of accomplishing the Exist and Find.
boolean tstFind = false;
foreach (parseAC item in pACList)
{
tstFind = pList.Exists(x => (x.CompanyId == item.key.ToString()));
if (tstFind == true)
{
pItem = pList.Find(x => (x.CompanyId == item.key.ToString()));
//Processing done here. pItem gets updated here
...
}
Just as a side note, I'm going to be researching a way to use joins to see if that is faster. But I haven't gotten there yet. The above code is my first cut at solving this issue and it appears to work. However, since I have the time I want to see if there is a better way still.
Any input is greatly appreciated.
Time Findings:
My current Find and Exists code takes about 84 minutes to loop through the 5.5M items in the pACList.
Using pList.firstOrDefault(x=> x.CompanyId == item.key.ToString()); takes 54 minutes to loop through 5.5M items in the pACList

You can retrieve item with FirstOrDefault instead of searching for item two times (first time to define if item exists, and second time to get existing item):
var tstFind = pList.FirstOrDefault(x => x.CompanyId == item.key.ToString());
if (tstFind != null)
{
//Processing done here. pItem gets updated here
}

Yes, use a hashtable so that your algorithm is O(n) instead of O(n*m) which it is right now.
var pListByCompanyId = pList.ToDictionary(x => x.CompanyId);
foreach (parseAC item in pACList)
{
if (pListByCompanyId.ContainsKey(item.key.ToString()))
{
pItem = pListByCompanyId[item.key.ToString()];
//Processing done here. pItem gets updated here
...
}

You can iterate though filtered list using linq
foreach (parseAC item in pACList.Where(i=>pList.Any(x => (x.CompanyId == i.key.ToString()))))
{
pItem = pList.Find(x => (x.CompanyId == item.key.ToString()));
//Processing done here. pItem gets updated here
...
}

Using lists for this type of operation is O(MxN) (M is the count of pACList, N is the count of pList). Additionally, you are searching pACList twice. To avoid that issue, use pList.FirstOrDefault as recommended by #lazyberezovsky.
However, if possible I would avoid using lists. A Dictionary indexed by the key you're searching on would greatly improve the lookup time.

Doing a linear search on the list for each item in another list is not efficient for large data sets. What is preferable is to put the keys into a Table or Dictionary that can be much more efficiently searched to allow you to join the two tables. You don't even need to code this yourself, what you want is a Join operation. You want to get all of the pairs of items from each sequence that each map to the same key.
Either pull out the implementation of the method below, or change Foo and Bar to the appropriate types and use it as a method.
public static IEnumerable<Tuple<Bar, Foo>> Merge(IEnumerable<Bar> pACList
, IEnumerable<Foo> pList)
{
return pACList.Join(pList, item => item.Key.ToString()
, item => item.CompanyID.ToString()
, (a, b) => Tuple.Create(a, b));
}
You can use the results of this call to merge the two items together, as they will have the same key.
Internally the method will create a lookup table that allows for efficient searching before actually doing the searching.

Convert pList to HashSet then query pHashSet.Contains(). Complexity O(N) + O(n)
Sort pList on CompanyId and do Array.BinarySearch() = O(N Log N) + O(n * Log N )
If Max company id is not prohibitively large, simply create and array of them where item with company id i exists at i-th position. Nothing can be more fast.
where N is size of pList and n is size of pACList

Efficient and Accurate way to add items into a TList

I have 2 lists and the entities of the those lists have some IDs for instance
Client.ID, where ID is a property of Client anf then I have PopulationClient.ID, where ID is a property of the class PopulationClient. So I have two Lists
TList<Client> clients = clientsHelper.GetAllClients();
TList<PopulationClient> populationClients = populationHelper.GetAllPopulationClients();
So then I have a temp List
TList<Client> temp_list = new TList<Client>();
So the problem i am having is doing this efficiently and correctly. This is what I have tried.. but I am not getting the correct results
foreach(PopulationClient pClients in populationClients)
{
foreach(Client client in clients)
{
if(pClients.ID != client.ID && !InTempList(temp_list, pClients.ID))
{
temp_list.Add(client);
}
}
}
public bool InTempList(TList<Client> c, int id)
{
bool IsInList = false;
foreach(Client client in c)
{
if(client.ID == id)
{
IsInList = true;
}
}
return IsInList;
}
So while I am trying to do it right I can not come up with a good way of doing it, this is not returning the correct data because in my statement in the first loop at the top,at some point one or more is different to the otherone so it adds it anyways. What constraints do you think I should check here so that I only end up with a list of Clients that are in population clients but not in Clients?.
For instance population clients would have 4 clients and Clients 2, those 2 are also in population clients but I need to get a list of population clients not in Clients.
ANy help or pointers would be appreciated.

First, let's concentrate on getting the right results, and then we'll optimize.
Consider your nested loops: you will get too many positives, because in most (pclient, client) pairs the IDs wouldn't match. I think you wanted to code it like this:
foreach(PopulationClient pClients in populationClients)
{
if(!InTempList(clients, pClients.ID) && !InTempList(temp_list, pClients.ID))
{
temp_list.Add(client);
}
}
Now for the efficiency of that code: InTempList uses linear search through lists. This is not efficient - consider using structures that are faster to search, for example, hash sets.

If I understand what you're looking for, here is a way to do it with LINQ...
tempList = populationList.Where(p => !clientList.Any(p2 => p2.ID == p.ID));

Just to offer another LINQ-based answer... I think your intent is to populate tempList based on all the items in 'clients' (returned from GetAllClients) that don't show up (based on 'ID" value) in the populationClients collection.
If that's the case, then I'm going to assume that populationClients is sufficiently large to warrant doing a hash-based looked (if it's less than 10 items, the linear scan may not be a big deal, for instance).
So we want a fast-lookup version of all the ID values from the populationClients collection:
var populationClientIDs = populationClients.Select(pc => pc.ID);
var populationClientIDHash = new HashSet(populationClientIDs);
Now that we have the ID values we want to ignore in a fast lookup data structure, we can then use that as a filter for the clients:
var filteredClients = clients.Where(c => populationClientIDHash.Contains(c.ID) == false);
Based on the usage/need, you could either populate the tempList from 'filteredClients', or do a ToList, or whatever.

Build Tree more efficiently?

I was wondering if this code is good enough or if there are glaring newbie no-no's.
Basically I'm populating a TreeView listing all Departments in my database. Here is the Entity Framework model:
Here is the code in question:
private void button1_Click(object sender, EventArgs e)
{
DepartmentRepository repo = new DepartmentRepository();
var parentDepartments = repo.FindAllDepartments()
.Where(d => d.IDParentDepartment == null)
.ToList();
foreach (var parent in parentDepartments)
{
TreeNode node = new TreeNode(parent.Name);
treeView1.Nodes.Add(node);
var children = repo.FindAllDepartments()
.Where(x => x.IDParentDepartment == parent.ID)
.ToList();
foreach (var child in children)
{
node.Nodes.Add(child.Name);
}
}
}
EDIT:
Good suggestions so far. Working with the entire collection makes sense I guess. But what happens if the collection is huge as in 200,000 entries? Wouldn't this break my software?
DepartmentRepository repo = new DepartmentRepository();
var entries = repo.FindAllDepartments();
var parentDepartments = entries
.Where(d => d.IDParentDepartment == null)
.ToList();
foreach (var parent in parentDepartments)
{
TreeNode node = new TreeNode(parent.Name);
treeView1.Nodes.Add(node);
var children = entries.Where(x => x.IDParentDepartment == parent.ID)
.ToList();
foreach (var child in children)
{
node.Nodes.Add(child.Name);
}
}

Since you are getting all of the departments anyway, why don't you do it in one query where you get all of the departments and then execute queries against the in-memory collection instead of the database. That would be much more efficient.
In a more general sense, any database model that is recursive can lead to issues, especially if this could end up being a fairly deep structure. One possible thing to consider would be for each department to store all of its ancestors so that you would be able to get them all at once instead of having to query for them all at once.

In light of your edit, you might want to consider an alternative database schema that scales to handle very large tree structures.
There's a explanation on the fogbugz blog on how they handle hierarchies. They also link to this article by Joe Celko for more information.
Turns out there's a pretty cool solution for this problem explained by Joe Celko. Instead of attempting to maintain a bunch of parent/child relationships all over your database -- which would necessitate recursive SQL queries to find all the descendents of a node -- we mark each case with a "left" and "right" value calculated by traversing the tree depth-first and counting as we go. A node's "left" value is set whenever it is first seen during traversal, and the "right" value is set when walking back up the tree away from the node. A picture probably makes more sense:
The Nested Set SQL model lets us add case hierarchies without sacrificing performance.
How does this help? Now we just ask for all the cases with a "left" value between 2 and 9 to find all of the descendents of B in one fast, indexed query. Ancestors of G are found by asking for nodes with "left" less than 6 (G's own "left") and "right" greater than 6. Works in all databases. Greatly increases performance -- particularly when querying large hierarchies.

Assuming that you are getting the data from a database the first thing that comes to mind is that you are going to be hitting the database n+1 times for as many parents that you have in the database. You should try and get the whole tree structure out in one hit.
Secondly, you seem to get the idea patterns seeing as you appear to be using the repository pattern so you might want to look at IoC. It allows you to inject your dependency on a particular object such as your repository into your class where it is going to be used allowing for easier unit testing.
Thirdly, regardless of where you get your data from, move the structuring of the data into a tree data structure into a service which returns you an object containing all your departments that have already been organised (This basically becomes a DTO). This will help you reduce code duplication.
With anything you need to apply the yagni principle. This basically says that you should only do something if you are going to need it so if the code you have provided above is complete, needs no further work and is functional don't touch it. The same goes with the performance issue of select n+1, if you are not seeing any performance hits don't do anything as it may be premature optimization.
In your edit
DepartmentRepository repo = new DepartmentRepository();
var entries = repo.FindAllDepartments();
var parentDepartments = entries.Where(d => d.IDParentDepartment == null).ToList();
foreach (var parent in parentDepartments)
{
TreeNode node = new TreeNode(parent.Name);
treeView1.Nodes.Add(node);
var children = entries.Where(x => x.IDParentDepartment == parent.ID).ToList();
foreach (var child in children)
{
node.Nodes.Add(child.Name);
}
}
You still have a n+1 issue. This is because the data is only retrieved from the database when you call the ToList() or when you iterate over the enumeration. This would be better.
var entries = repo.FindAllDepartments().ToList();
var parentDepartments = entries.Where(d => d.IDParentDepartment == null);
foreach (var parent in parentDepartments)
{
TreeNode node = new TreeNode(parent.Name);
treeView1.Nodes.Add(node);
var children = entries.Where(x => x.IDParentDepartment == parent.ID);
foreach (var child in children)
{
node.Nodes.Add(child.Name);
}
}

That looks ok to me, but think about a collection of hundreds of thousands nodes. The best way to do that is asynchronous loading - please notice, that do don't necassarily have to load all elements at the same time. Your tree view can be collapsed by default and you can load additional levels as the user expands tree's nodes. Let's consider such case: you have a root node containing 100 nodes and each of these nodes contains at least 1000 nodes. 100 * 1000 = 100000 nodes to load - pretty much, istn't it? To reduce the database traffic you can first load your first 100 nodes and then, when user expands one of those, you can load its 1000 nodes. That will save considerable amount of time.

Things that come to mind:
It looks like .ToList() is needless. If you are simply iterating over the returned result, why bother with the extra step?
Move this function into its own thing and out of the event handler.
As other have said, you could get the whole result in one call. Sort by IDParentDepartment so that the null ones are first. That way, you should be able to get the list of departments in one call and iterate over it only once adding children departments to already existing parent ones.

Wrap the TreeView modifications with:
treeView.BeginUpdate();
// modify the tree here.
treeView.EndUpdate();
To get better performance.
Pointed out here by jgauffin

This should use only one (albeit possibly large) call to the database:
Departments.Join(
Departments,
x => x.IDParentDepartment,
x => x.Name,
(o,i) => new { Child = o, Parent = i }
).GroupBy(x => x.Parent)
.Map(x => {
var node = new TreeNode(x.Key.Name);
x.Map(y => node.Nodes.Add(y.Child.Name));
treeView1.Nodes.Add(node);
}
)
Where 'Map' is just a 'ForEach' for IEnumerables:
public static void Map<T>(this IEnumerable<T> source, Action<T> func)
{
foreach (T i in source)
func(i);
}
Note: This will still not help if the Departments table is huge as 'Map' materializes the result of the sql statement much like 'ToList()' does. You might consider Piotr's answer.

In addition to Bronumski and Keith Rousseau answer
Also add the DepartmentID with the nodes(Tag) so that you don't have to re-query the database to get the departmentID

LINQ to Entities Question - All objects where all items in subcollection appear in another collection?

Hopefully I can explain this to where it make sense, but I'm trying to get a list of objects out of a master list using a speicific and complex (complex to me, at least) set of criteria.
I have a Class called TableInfo that exposes a List of ForeignKeyInfo. ForeignKeyInfo has a string property (among others) called, Table. I need to do some sequential processing using my TableInfo objects but only work with the TableInfo objects I haven't yet processed. To keep track of which TableInfo objects have already been processed I have a List which stores the name of the table after the processing has been complete.
I want to loop until all of the items in my TableInfo collection appear in my processed list. For each iteration of the loop, I should be processing all of the TableInfo items where all of the ForeignKeyInfo.Table strings appear in my processed List.
Here's how I've written it in "standard" looping code:
while(processed.Count != _tables.Count)
{
List<TableInfo> thisIteration = new List<TableInfo>();
foreach (TableInfo tab in _tables)
{
bool allFound = true;
foreach (ForeignKeyInfo fk in tab.ForeignKeys)
{
allFound = allFound && processed.Contains(fk.Table);
}
if (allFound && !processed.Contains(tab.Name))
{
thisIteration.Add(tab);
}
}
//now do processing using thisIteration list
//variable, "thisIteration", is what I'd like to replace with the result from LINQ
}

This should do it:
var thisIteration = _tables.Where(t => !processed.Contains(t.Name)
&& t.ForeignKeys
.All(fk => processed.Contains(fk.Table));
I'm assuming you just need to iterate over the thisIteration collection, in which case leaving it as an IEnumerable is fine. If you need it to be a list, you can just put in a .ToList() call at the end.

I'm not really sure what you're trying to do here. However, you can convert the body of your loop into the following LINQ query, if that makes things simpler...
List<TableInfo> thisIteration = (from tab in _tables
let allFound = tab.ForeignKeys.Aggregate(true, (current, fk) => current && processed.Contains(fk.Table))
where allFound && !processed.Contains(tab.Name)
select tab).ToList();