I have multiple instances of my application. each application is pointing to its own solr for document indexing.
I am working on a unified search, where user hit a query in the search bar and the relevant documents from all the instance should be ranked based on relevance.
Right now I have implemented a solution based on Round Robin fashion.
For example, I have 2 instances, Ins-1 with solr-1 and Ins-2 with solr-2.
Ins-1 has 1K docs and Ins-2 has 5K docs. when I hit any query, the query will fetch X number of docs from solr-1 and X number of docs from solr-2.
I am showing those 2X documents in round robin fashion. But it is not a best way to show the search result.
I am looking for a solution where I can re-rank those 2X documents based on relevance to the search.
I think you should merge the two instances into single instance. You can import data from one instance to another. Solr Admin UI has a tab 'DataImport' to import data from one collection to another.
here doc1 and doc2 are two invidual responses from solr you can do it in JAVA
SolrDocumentList appendResponse(SolrDocumentList doc1,SolrDocumentList doc2) {
SolrDocumentList documentsList=new SolrDocumentList();
for (SolrDocument solrDocument:doc1)
{
documentsList.add(solrDocument);
}
for (SolrDocument solrDocument:doc2)
{
documentsList.add(solrDocument);
}
return documentsList;
}
Related
Let's use the classic example of blog context. In our domain we have the following scenarios: Users can write Posts. Posts must be cataloged at least in one Category. Posts can be described using Tags. Users can comment on Posts.
The four entities (Post, Category, Tag, Comment) are implemented as different aggregates because of I have not detected any rule for that an entity data should interfere in another. So, for each aggregate I will have one repository that represent it. Too, each aggregate reference others by his id.
Following CQRS, from this scenario I have deducted typical use cases that result on commands such as WriteNewPostCommand, PublishPostCommand, DeletePostCommand etc... along with their respective queries to get data from repositories. FindPostByIdQuery, FindTagByTagNameQuery, FindPostsByAuthorIdQuery etc...
Depending on which site of the app we are (backend or fronted) we will have queries more or less complex. So, if we are on the front page maybe we need build some widgets to get last comments, latest post of a category, etc... Queries that involve a simple Query object (few search criterias) and a QueryHandler very simple (a single repository as dependency on the handler class)
But in other places this queries can be more complex. In an admin panel we require to show in a table a relation that satisfy a complex search criteria. Might be interesting search posts by: author name (no id), categories names, tags name, publish date... Criterias that belongs to different aggregates and different repositories.
In addition, in our table of post we dont want to show the post along with author ID, or categories ID. We need to show all information (name user, avatar, category name, category icon etc).
My questions are:
At infrastructure layer, when we design repositories, the search methods (findAll, findById, findByCriterias...), should have return the corresponding entity referencing to all associations id's? I mean, If a have a method findPostById(uuid) or findPostByCustomFilter(filter), should return a post instance with a reference to all categories id it has, all tags id, and author id that it has? Or should my repo have some kind of method that populates a given post instance with the associations I want?
If I want to search posts created from 12/12/2014, written by John, and categorised on "News" and "Videos" categories and tags "sci-fi" and "adventure", and get the full details of each aggregate, how should create my Query and QueryHandler?
a) Create a Query with all my parameters (authorName, categoriesNames, TagsNames, if a want retrive User, Category, Tag association full detailed) and then his QueryHandler ensamble the different read models in a only one. Or...
b) Create different Queries (FindCategoryByName, FindTagByName, FindUserByName) and then my web controller calls them for later
call to FindPostQuery but now passing him the authorid, categoryid, tagid returned from the other queries?
The b) solution appear more clean but it seems me more expensive.
On the query side, there are no entities. You are free to populate your read models in any way suits your requirements best. Whatever data you need to display on (a part of) the screen, you put it in the read model. It's not the command side repositories that return these read models but specialized query side data access objects.
You mentioned "complex search criteria" -- I recommend you model it with a corresponding SearchCriteria object. This object would be technnology agnostic, but it would be passed to your Query side data access object that would know how to combine the criteria to build a lower level query for the specific data store it's targeted at.
With simple applications like this, it's easier to not get distracted by aggregates. Do event sourcing, subscribe to the events by one set of tables that is easy to query the way you want.
Another words, it sounds like you're main goal is to be able to query easily for the scenarios you describe. Start with that end goal. Now write your event handler to adjust your tables accordingly.
Start with events and the UI. Then everything else will fit easily. Google "Event Modeling" as it will help you formulate ideas sound what and how you want to build these style of applications.
I can see three problems in your approach and they need to be solved separately:
In CQRS the Queries are completely separate from the Commands. So, don't try to solve your queries with your Commands pipelines repositories. The point of CQRS is precisely to allow you to solve the commands and queries in very different ways, as they have very different requirements.
You mention DDD in the question title, but you don't mention your Bounded Contexts in the question itself. If you follow DDD, you'll most likely have more than one BC. For example, in your question, it could be that CategoryName and AuthorName belong to two different BCs, which are also different from the BC where the blog posts are. If that is the case and each BC properly owns its own data, the data that you want to search by and show in the UI will be stored potentially in different databases, therefore implementing a query in the DB with a join might not even be possible.
Searching and Reading data are two different concerns and can/should be solved differently. When you search, you get some search criteria (including sorting and paging) and the result is basically a list of IDs (authorIds, postIds, commentIds). When you Read data, you get one or more Ids and the result is one or more DTOs with all the required data properties. It is normal that you need to read data from multiple BCs to populate a single page, that's called UI composition.
So if we agree on these 3 points and especially focussing on point 3, I would suggest the following:
Figure out all the searches that you want to do and see if you can decompose them to simple searches by BC. For example, search blog posts by author name is a problem, because the author information could be in a different BC than the blog posts. So, why not implement a SearchAuthorByName in the Authors BC and then a SearchPostsByAuthorId in the Posts BC. You can do this from the Client itself or from the API. Doing it in the client gives the client a lot of flexibility because there are many ways a client can get an authorId (from a MyFavourites list, from a paginated list or from a search by name) and then get the posts by authorId is a separate operation. You can do the same by tags, categories and other things. The Post will have Ids, but not the extra details about those IDs.
Potentially, you might want more complicated searches. As long as the search criteria (including sorting fields) contain fields from a single BC, you can easily create a read model and execute the search there. Note that this is only for the search criteria. If the search result needs data from multiple BCs you can solve it with UI composition. But if the search criteria contain fields from multiple BCs, then you'll need some sort of Search engine capable of indexing data coming from multiple sources. This is especially evident if you want to do full-text search, search by categories, tags, etc. with large quantities of data. You will need to use some specialized service like Elastic Search and it won't belong to any of your existing BCs, it'll be like a supporting service.
From CQRS you will have a separeted Stack for Queries and Commands. Your query stack should represent a diferente module, namespace, dll or package at your project.
a) You will create one QueryModel and this query model will return whatever you need. If you are familiar with Entity Framework or NHibernate, you will create a Façade to hold this queries togheter, DbContext or Session.
b) You can create this separeted queries, but saying again, if you are familiar with any ORM your should return the set that represents the model, return every set as IQueryable and use LET (Linq Expression Trees) to make your Query stack more dynamic.
Using Entity Framework and C# for exemple:
public class QueryModelDatabase : DbContext, IQueryModelDatabase
{
public QueryModelDatabase() : base("dbname")
{
_products = base.Set<Product>();
_orders = base.Set<Order>();
}
private readonly DbSet<Order> _orders = null;
private readonly DbSet<Product> _products = null;
public IQueryable<Order> Orders
{
get { return this._orders.Include("Items").Include("Items.Product"); }
}
public IQueryable<Product> Products
{
get { return _products; }
}
}
Then you should do queries the way you need and return anything:
using (var db = new QueryModelDatabase())
{
var queryable = from o in db.Orders.Include(p => p.Items).Include("Details.Product")
where o.OrderId == orderId
select new OrderFoundViewModel
{
Id = o.OrderId,
State = o.State.ToString(),
Total = o.Total,
OrderDate = o.Date,
Details = o.Items
};
try
{
var o = queryable.First();
return o;
}
catch (InvalidOperationException)
{
return new OrderFoundViewModel();
}
}
How the search everything kind of application is indexing & keeping track of data into its search indexes.
Recently I have been working on Apache Solr which is producing amazing results for a search. But it was for one particular products catalog section that is being searched. As Solr is a stores it's data document, we indexed searchable fields as document in solr. I'm not sure how it can be used to build a search everything kind of search? And how should I index data into Solr?
By search everything I mean, to search into different module for information like Customers, Services, Accounts, Orders, Catalog, Support Ticket, etc. So search return results which is combined as a result from a single search form and user don't need to go into different forms for search that module?
Do I need to build different indexes for each such data models or store them into solr as single document? What is the best strategy to implement this.
You can store all that data in a single index with each document having an extra field that stores its type (Customer, Order, etc.). For the within-module search, just restrict the search query to documents of that type. For the Search All functionality, use copyField to copy all the relevant fields in each document type into one big field, and search with the document type field unconstrained.
I am using the AdvancedDatabaseCrawler as a base for my search page. I have configured it so that I can search for what I want and it is very fast. The problem is that as soon as you want to do anything with the search results that requires accessing field values the performance goes through the roof.
The main search results part is fine as even if there are 1000 results returned from the search I am only showing 10 or 20 results per page which means I only have to retrieve 10 or 20 items. However in the sidebar I am listing out various filtering options with the number or results associated with each filtering option (eBay style). In order to retrieve these filter options I perform a relationship search based on the search results. Since the search results only contain SkinnyItems it has to call GetItem() on every single result to get the actual item in order to get the value that I'm filtering by. In other words it will call Database.GetItem(id) 1000 times! Obviously that is not terribly efficient.
Am I missing something here? Is there any way to configure Sitecore search to retrieve custom values from the search index? If I can search for the values in the index why can't I also retrieve them? If I can't, how else can I process the results without getting each individual item from the database?
Here is an idea of the functionality that I’m after: http://cameras.shop.ebay.com.au/Digital-Cameras-/31388/i.html
Klaus answered on SDN: use facetting with Apache Solr or similar.
http://sdn.sitecore.net/SDN5/Forum/ShowPost.aspx?PostID=35618
I've currently resolved this by defining dynamic fields for every field that I will need to filter by or return in the search result collection. That way I can achieve the facetted searching that is required without needing to grab field values from the database. I'm assuming that by adding the dynamic fields we are taking a performance hit when rebuilding the index. But I can live with that.
In the future we'll probably look at utilizing a product like Apache Solr.
Looking at the example described in Couch DB Joins.
It discusses view collation and how you can have one document for your blog posts, and then each comment is a separate document in CouchDB. So for example, I could have "My Post" and 5 comments associated with "My Post" for a total of 6 documents. In their example, "myslug" is stored both in the post document, and each comment document, so that when I search CouchDB with the key "myslug" it returns all the documents.
Here's the problem/question. Let's say I want to search on the author in the comments and a post that also has a category of "news". How would this work exactly?
So for example:
function(doc) {
if (doc.type == "post") {
emit([doc._id, 0], doc);
} else if (doc.type == "comment") {
emit([doc.post, 1], doc);
}
}
That will load my blog post and comments based on this: ?startkey=["myslug"]
However, I want to do this, grab the comments by author bob, and the post that has the category news. For this example, bob has written three comments to the blog post with the category news. It seems as if CouchDB only allows me search on keys that exist in both documents, and not search on a key in one document, and a key in another that are "joined" together with the map function.
In other words, if post and comments are joined by a slug, how do I search on one field in one document and another field in another document that are joined by the id aka. slug?
In SQL it would be something like this:
SELECT * FROM comments JOIN doc.id ON doc.post WHERE author = bob AND category = news
I've been investigating couchdb for about a week so I'm hardly qualified to answer your question, but I think I've come to the conclusion it can't be done. View results need to be tied to one and only one document so the view can be updated. You are going to have to denormalize, at least if you don't want to do a grunt search. If anyone's come up with a clever way to do this I'd really like to know.
There are several ways that you can approximate a SQL join on CouchDB. I've just asked a similar question here: Why is CouchDB's reduce_limit enabled by default? (Is it better to approximate SQL JOINS in MapReduce views or List views?)
You can use MapReduce (not a good option)
You can use lists (This will iterate over a result set before emitting results, meaning you can 'combine' documents in a number of creative ways)
You can also apparently use 'collation', though I haven't figured this out yet (seems like I always get a count and can only use the feature with Reduce - if I'm on the right track)
I have three document types MainCategory, Category, SubCategory... each have a parentid which relates to the id of their parent document.
So I want to set up a view so that I can get a list of SubCategories which sit under the MainCategory (preferably just using a map function)... I haven't found a way to arrange the view so this is possible.
I currently have set up a view which gets the following output -
{"total_rows":16,"offset":0,"rows":[
{"id":"11098","key":["22056",0,"11098"],"value":"MainCat...."},
{"id":"11098","key":["22056",1,"11098"],"value":"Cat...."},
{"id":"33610","key":["22056",2,"null"],"value":"SubCat...."},
{"id":"33989","key":["22056",2,"null"],"value":"SubCat...."},
{"id":"11810","key":["22245",0,"11810"],"value":"MainCat...."},
{"id":"11810","key":["22245",1,"11810"],"value":"Cat...."},
{"id":"33106","key":["22245",2,"null"],"value":"SubCat...."},
{"id":"33321","key":["22245",2,"null"],"value":"SubCat...."},
{"id":"11098","key":["22479",0,"11098"],"value":"MainCat...."},
{"id":"11098","key":["22479",1,"11098"],"value":"Cat...."},
{"id":"11810","key":["22945",0,"11810"],"value":"MainCat...."},
{"id":"11810","key":["22945",1,"11810"],"value":"Cat...."},
{"id":"33123","key":["22945",2,"null"],"value":"SubCat...."},
{"id":"33453","key":["22945",2,"null"],"value":"SubCat...."},
{"id":"33667","key":["22945",2,"null"],"value":"SubCat...."},
{"id":"33987","key":["22945",2,"null"],"value":"SubCat...."}
]}
Which QueryString parameters would I use to get say the rows which have a key that starts with ["22945".... When all I have (at query time) is the id "11810" (at query time I don't have knowledge of the id "22945").
If any of that makes sense.
Thanks
The way you store your categories seems to be suboptimal for the query you try to perform on it.
MongoDB.org has a page on various strategies to implement tree-structures (they should apply to Couch and other doc dbs as well) - you should consider Array of Ancestors, where you always store the full path to your node. This makes updating/moving categories more difficult, but querying is easy and fast.