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Retrieving and deserializing large lists of Redis-cache items

We're planning to add a Redis-cache to an existing solution.
We have this core entity which is fetched a lot, several times per session. The entity consists of 13 columns where the majority is less than 20 characters. Typically it's retrieved by parent id, but sometimes as a subset that is fetched by a list of ids. To solve this we're thinking of implementing the solution below, but the question is if it's a good idea? Typically the list is around 400 items, but in some cases it could be up to 3000 items.
We would store the instances in the list with this key pattern: EntityName:{ParentId}:{ChildId}, where ParentId and ChildId is ints.
Then to retrieve the list based on ParentId we would call the below method with EntityName:{ParentId}:* as the value of the pattern-argument:
public async Task<List<T>> GetMatches<T>(string pattern)
{
var keys = _multiPlexer.GetServer(_multiPlexer.GetEndPoints(true)[0]).Keys(pattern: pattern).ToArray();
var values = await Db.StringGetAsync(keys: keys);
var result = new List<T>();
foreach (var value in values.Where(x => x.HasValue))
{
result.Add(JsonSerializer.Deserialize<T>(value));
}
return result;
}
And to retrieve a specific list of items we would call the below method with a list of exact keys:
public async Task<List<T>> GetList<T>(string[] keys)
{
var values = await Db.StringGetAsync(keys: keys.Select(x => (RedisKey)x).ToArray());
var result = new List<T>();
foreach (var value in values.Where(x => x.HasValue))
{
result.Add(JsonSerializer.Deserialize<T>(value));
}
return result;
}
The obvious worry here is the amount of objects to deserialize and the performance of System.Text.Json.
A alternative to this would be to store the data twice, both as a list and on it's own, but that would only help in the case where we're fetching by ParentId. We could also only store the data as a list and retrieve it every time only to sometimes use a subset.
Is there a better way to tackle this?
All input is greatly appreciated! Thanks!
Edit
I wrote a small console application to load test the alternatives, fetching 2000 items 100 times took 2020ms with the pattern matching and fetching the list took 1568ms. I think we can live with that difference and go with the pattern matching.

It seems like #Xerillio was right. I did some load testing using hosted services and then it was almost three times slower to fetch the list using the pattern matching, slower then receiving the list directly from SQL. So, to answer my own question if it's a good idea, I would say no it isn't. The majority of the added time was not because of deserialization rather because of fetching the keys using the pattern matching.
Here's the result from fetching 2000 items 100 items in a loop:
Fetch directly from db = 8625ms
Fetch using list of exact keys = 5663ms
Fetch using match = 13098ms
Fetch full list = 5352ms

LINQ Optimization for searching a if an object exist in a list within a list

Currently I have 7,000 video entries and I have a hard time optimizing it to search for Tags and Actress.
This is my code I am trying to modify, I tried using HashSet. It is my first time using it but I don't think I am doing it right.
Dictionary dictTag = JsonPairtoDictionary(tagsId,tagsName);
Dictionary dictActresss = JsonPairtoDictionary(actressId, actressName);
var listVid = new List<VideoItem>(db.VideoItems.ToList());
HashSet<VideoItem> lll = new HashSet<VideoItem>(listVid);
foreach (var tags in dictTag)
{
lll = new HashSet<VideoItem>(lll.Where(q => q.Tags.Exists(p => p.Id == tags.Key)));
}
foreach (var actress in dictActresss)
{
listVid = listVid.Where(q => q.Actress.Exists(p => p.Id == actress.Key)).ToList();
}
First part I get all the Videos in Db by using db.VideoItems.ToList()
Then it will go through a loop to check if a Tag exist
For each VideoItem it has a List<Tags> and I use 'exist' to check if a tag is match.
Then same thing with Actress.
I am not sure if its because I am in Debug mode and ApplicationInsight is active but it is slow. And I will get like 10-15 events per second with baseType:RemoteDependencyData which I am not sure if it means it still connected to database (should not be since I only should only be messing with the a new list of all videos) or what.
After 7 mins it is still processing and that's the longest time I have waited.
I am afraid to put this on my live site since this will eat up my resource like candy

Instead of optimizing the linq you should optimize your database query.
Databases are great at optimized searches and creating subsets and will most likely be faster than anything you write. If you have need to create a subset based on more than on database parameter I would recommend looking into creating some indexes and using those.
Edit:
Example of db query that would eliminate first for loop (which is actually multiple nested loops and where the time delay comes from):
select * from videos where tag in [list of tags]
Edit2
To make sure this is most efficient, require the database to index on the TAGS column. To create the index:
CREATE INDEX video_tags_idx ON videos (tag)
Use 'explains' to see if the index is being used automatically (it should be)
explain select * from videos where tag in [list of tags]
If it doesn't show your index as being used you can look up the syntax to force the use of it.

The problem was not optimization but it was utilization of the Microsoft SQL or my ApplicationDbContext.
I found this when I realize that http://www.albahari.com/nutshell/predicatebuilder.aspx
Because the problem with Keyword search, there can be multiple keywords, and the code I made above doesn't utilize the SQL which made the long execution time.
Using the predicate builder, it will be possible to create dynamic conditions in LINQ

Fast random access to a collection

I'm consuming a stream of semi-random tokens. For each token, I'm maintaining a lot of data (including some sub-collections).
The number of unique tokens is unbounded but in practice tends to be on the order of 100,000-300,000.
I started with a list and identified the appropriate token object to update using a Linq query.
public class Model {
public List<State> States { get; set; }
...
}
var match = model.States.Where(x => x.Condition == stateText).SingleOrDefault();
Over the first ~30k unique tokens, I was able to find and update ~1,100 tokens/sec.
Performance analysis shows that 85% of the total Cpu cycles are being spent on the Where(...).SingleOrDefault() (which makes sense, lists are inefficient way to search).
So, I switched the list over to a HashSet and profiled again, confident that HashSet would be able to random seek faster. This time, I was only processing ~900 tokens/sec. And a near-identical amount of time was spent on the Linq (89%).
So... First up, am I misusing the HashSet? (Is using Linq is forcing a conversion to IEnumerable and then an enumeration / something similar?)
If not, what's the best pattern to implement myself? I was under the impression that HashSet already does a Binary seek so I assume I'd need to build some sort of tree structure and have smaller sub-sets?
To answer some questions form comments... The condition is unique (if I get the same token twice, I want to update the same entry), the HashSet is the stock .Net implementation (System.Collections.Generic.HashSet<T>).
A wider view of the code is...
var state = new RollingList(model.StateDepth); // Tracks last n items and drops older ones. (Basically an array and an index that wraps around
var tokens = tokeniser.Tokenise(contents); // Iterator
foreach (var token in tokens) {
var stateText = StateToString(ref state);
var match = model.States.Where(x => x.Condition == stateText).FirstOrDefault();
// ... update the match as appropriate for the token
}

var match = model.States.Where(x => x.Condition == stateText).SingleOrDefault();
If you're doing that exact same thing with a hash set, that's no savings. Hash sets are optimized for quickly answering the question "is this member in the set?" not "is there a member that makes this predicate true in the set?" The latter is linear time whether it is a hash set or a list.
Possible data structures that meet your needs:
Make a dictionary mapping from text to state, and then do a search in the dictionary on the text key to get the resulting state. That's O(1) for searching and inserting in theory; in practice it depends on the quality of the hash.
Make a sorted dictionary mapping from text to state. Again, search on text. Sorted dictionaries keep the keys sorted in a balanced tree, so that's O(log n) for searching and inserting.

30k is not that much so if state is unique you can do something like this.
Dictionary access is much faster.
var statesDic = model.States.ToDictionary(x => x.Condition, x => x);
var match = statesDic.ConstainsKey(stateText) ? statesDic[stateText] : default(State);
Quoting MSDN:
The Dictionary generic class provides a mapping from a set of keys to a set of values. Each addition to the dictionary consists of a value and its associated key. Retrieving a value by using its key is very fast, close to O(1), because the Dictionary class is implemented as a hash table.
You can find more info about Dictionaries here.
Be also aware that Dictionaries use memory space to improve performance, you can do a quick test for 300k items and see what kind of space I'm talking about like this:
var memoryBeforeDic = GC.GetTotalMemory(true);
var dic = new Dictionary<string,object>(300000);
var memoryAfterDic = GC.GetTotalMemory(true);
Console.WriteLine("Memory: {0}", memoryAfterDic - memoryBeforeDic);

What is the fastest way to search a List<T> across multiple properties?

I have a process I've inherited that I'm converting to C# from another language. Numerous steps in the process loop through what can be a lot of records (100K-200K) to do calculations. As part of those processes it generally does a lookup into another list to retrieve some values. I would normally move this kind of thing into a SQL statement (and we have where we've been able to) but in these cases there isn't really an easy way to do that. In some places we've attempted to convert the code to a stored procedure and decided it wasn't working nearly as well as we had hoped.
Effectively, the code does this:
var match = cost.Where(r => r.ryp.StartsWith(record.form.TrimEnd()) &&
r.year == record.year &&
r.period == record.period).FirstOrDefault();
cost is a local List type. If I was doing a search on only one field I'd probably just move this into a Dictionary. The records aren't always unique either.
Obviously, this is REALLY slow.
I ran across the open source library I4O which can build indexes, however it fails for me in various queries (and I don't really have the time to attempt to debug the source code). It also doesn't work with .StartsWith or .Contains (StartsWith is much more important since a lot of the original queries take advantage of the fact that doing a search for "A" would find a match in "ABC").
Are there any other projects (open source or commercial) that do this sort of thing?
EDIT:
I did some searching based on the feedback and found Power Collections which supports dictionaries that have keys that aren't unique.
I tested ToLookup() which worked great - it's still not quite as fast as the original code, but it's at least acceptable. It's down from 45 seconds to 3-4 seconds. I'll take a look at the Trie structure for the other look ups.
Thanks.

Looping through a list of 100K-200K items doesn't take very long. Finding matching items within the list by using nested loops (n^2) does take long. I infer this is what you're doing (since you have assignment to a local match variable).
If you want to quickly match items together, use .ToLookup.
var lookup = cost.ToLookup(r => new {r.year, r.period, form = r.ryp});
foreach(var group in lookup)
{
// do something with items in group.
}
Your startswith criteria is troublesome for key-based matching. One way to approach that problem is to ignore it when generating keys.
var lookup = cost.ToLookup(r => new {r.year, r.period });
var key = new {record.year, record.period};
string lookForThis = record.form.TrimEnd();
var match = lookup[key].FirstOrDefault(r => r.ryp.StartsWith(lookForThis))
Ideally, you would create the lookup once and reuse it for many queries. Even if you didn't... even if you created the lookup each time, it will still be faster than n^2.

Certainly you can do better than this. Let's start by considering that dictionaries are not useful only when you want to query one field; you can very easily have a dictionary where the key is an immutable value that aggregates many fields. So for this particular query, an immediate improvement would be to create a key type:
// should be immutable, GetHashCode and Equals should be implemented, etc etc
struct Key
{
public int year;
public int period;
}
and then package your data into an IDictionary<Key, ICollection<T>> or similar where T is the type of your current list. This way you can cut down heavily on the number of rows considered in each iteration.
The next step would be to use not an ICollection<T> as the value type but a trie (this looks promising), which is a data structure tailored to finding strings that have a specified prefix.
Finally, a free micro-optimization would be to take the TrimEnd out of the loop.
Now certainly all of this only applies to the specific example given and may need to be revisited due to other specifics of your situation, but in any case you should be able to extract practical gain from this or something similar.

What is the most efficient way to do look-up table in C#

What is the most efficient way to do look-up table in C#
I have a look-up table. Sort of like
0 "Thing 1"
1 "Thing 2"
2 "Reserved"
3 "Reserved"
4 "Reserved"
5 "Not a Thing"
So if someone wants "Thing 1" or "Thing 2" they pass in 0 or 1. But they may pass in something else also.
I have 256 of these type of things and maybe 200 of them are reserved.
So what is the most efficient want to set this up?
A string Array or dictionary variable that gets all of the values. And then take the integer and return the value at that place.
One problem I have with this solution is all of the "Reserved" values. I don't want to create those redundant "reserved" values. Or else I can have an if statement against all of the various places that are "reserved" but they might now be just 2-3, might be 2-3, 40-55 and all different places in the byte. This if statement would get unruly quick
My other option that I was thinking was a switch statement. And I would have all of the 50ish known values and would fall through through and default for the reserved values.
I am wondering if this is a lot more processing than creating a string array or dictionary and just returning the appropriate value.
Something else? Is there another way to consider?

"Retrieving a value by using its key is very fast, close to O(1), because the Dictionary(TKey, TValue) class is implemented as a hash table."
var things = new Dictionary<int, string>();
things[0]="Thing 1";
things[1]="Thing 2";
things[4711]="Carmen Sandiego";

The absolute fastest way to do lookups of integer values in C# is with an array. This will be preferable to using a dictionary, maybe, if you are trying to do tens of thousands of lookups at a time. For most purposes, this is overkill; it's more likely that you need to optimize developer time than processor time.
If the reserved keys are not simply all keys that aren't in the lookup table (i.e. if a lookup for a key can return the found value, a not-found status, or a reserved status), you'll need to save the reserved keys somewhere. Saving them as dictionary entries with magic values (e.g. the key of any dictionary entry whose value is null is reserved) is OK unless you write code that iterates over the dictionary's entries without filtering them.
A way to solve that problem is to use a separate HashSet<int> to store the reserved keys, and maybe bake the whole thing into a class, e.g.:
public class LookupTable
{
public readonly Dictionary<int, string> Table { get; }
public readonly HashSet<int> ReservedKeys { get; }
public LookupTable()
{
Table = new Dictionary<int, string>();
ReservedKeys = new HashSet<int>();
}
public string Lookup(int key)
{
return (ReservedKeys.Contains(key))
? null
: Table[key];
}
}
You'll note that this still has the magic-value issue - Lookup returns null if the key is reserved, and throws an exception if it's not in the table - but at least now you can iterate over Table.Values without filtering magic values.

Checkout the HybridDictionary. It automatically adjusts it's underlying storage mechanism based on size to get the greatest efficiency.
http://msdn.microsoft.com/en-us/library/system.collections.specialized.hybriddictionary.aspx

If you have lots of reserved (currently unused) values or if the range of the integer values can get very big, then I would use a generic dictionary (Dictionary):
var myDictionary = new Dictionary<int, string>();
myDictionary.Add(0, "Value 1");
myDictionary.Add(200, "Another value");
// and so on
Otherwise, if you have a fixed number of values and only few of the are currently unused, then I'd use a string array (string[200]) and set/leave the reserved entries to null.
var myArray = new string[200];
myArray[0] = "Value 1";
myArray[2] = "Another value";
//myArray[1] is null

The in-built Dictionary object (preferably a generic dictionary) would be ideal for this, and is specifically designed for fast/efficient retrieval of the values relating to the keys.
From the linked MSDN article:
Retrieving a value by using its key is
very fast, close to O(1), because the
Dictionary<(Of <(TKey, TValue>)>)
class is implemented as a hash table.
As far as your "reserved" keys go, I wouldn't worry about that at all if we're only talking about a few hundred keys/values. It's only when you reach tens, maybe hundreds of thousands of "reserved" keys/values that you'll want to implement something more efficient.
In those cases, probably the most efficient storage container then would be an implementation of a Sparse Matrix.

I'm not quite sure I understand your problem correctly. You have a collection of strings. Each string is associated to an index. The consumer requests gives an index and you return the corresponding string, unless the index is reserved. Right?
Can't you simple set reserved items as null in the array.
If not, using a dictionary that doesn't contain the reserved items seems a reasonable solution.
Anyway, you'll probably get better answers if you clarify your problem.

I would use a Dictionary to do the lookups. This is the most efficient way to do look ups by far. Using a string will run somewhere in the region of O(n) to find the object.
It might be useful to have a 2nd Dictionary to all you to do a reverse lookup if its needed

Load all your values into
var dic = new Dictionary<int, string>();
And use this for retrieval:
string GetDescription(int val)
{
if(0 <= val && val < 256)
if(!dic.Contains(val))
return "Reserved";
return dic[val];
throw new ApplicationException("Value must be between 0 and 255");
}

Your question seems to imply that the query key is an integer. Since you have at most 256 items, then the query key is in the range 0..255, right? If so, just have a string array of 256 strings, and use the key as an index into the array.
If your query key is a string value, then it's more like a real lookup table. Using a Dictionary object is simple, but if you're after raw speed for a set of as few as 50 or so actual answers, a do-it-yourself approach such as binary search, or a trie, could be quicker. If you use binary search, since the number of items is so small, you could unroll it.
How often does the list of items change? If it only changes very seldom, you can get even better speed by generating code to do the search, which you can then compile and execute to do each query.
On the other hand, I assume you've proven that this lookup is your bottleneck, either by profiling or taking stackshots. If less than 10% of time-when-slow is spent in this query, then it is not your bottleneck so you may as well do the thing that is easiest to code.