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Graphql faceted search

Providing an easy and practical way for shoppers to search your products is of critical importance in eCommerce. In many cases, online stores are no less than a labyrinth: hard to navigate, complicated logic, and nearly impossible to places to stumble across one product in the midst of hundreds of near-identical products — this is why you need faceted search.

Oftentimes, they will only know a few parameters and execute a query in order to get a list of products to look through. Your search and ranking algorithm must be good enough to help them. Using filters is the most basic, and efficient, way to do this. A more advanced method encompasses using faceted navigation and faceted search more on the distinction shortly together with a user-friendly, not overly complicated interface.

Faceted search or navigation is related to filters, but the phrases are not interchangeable as the former is a more flexible and efficient solution.

Faceting means creating a complex structure in which shoppers are presented with a smart, logical interface that makes it easier for them to get to the desired products.

Making search easier and faster, faceted search also helps enforce purchase decisions and lower site abandonment ratesleading to higher conversion rates and overall profit. Faceted search offers a chance to use filters in a smart way. Traditionally, simple filters are used for site-wide searches: to narrow down results to a certain category, brand etc.

With faceted searchyou can actually recommend even more relevant filters to users. If you have thousands of products in your store, you most likely have tens of thousands of individual attributes associated with them. It would be counterproductive and impossible to provide them all as filter options. But based on queries and results, you can help shoppers narrow down their scope by providing relevant filters.

For example, if a shopper runs a site-wide search and 8 out of the 10 most relevant results are in the same category, you can provide a filter that focuses on that category and add additional ones for the most common attributes acting here as product-specific filters in that category.

This can significantly improve user experience as it gets as close to actually reading their thoughts as search technology can get today. The point is to provide a better shopping experience. It also provides the user with a sense of control without making the shopping experience too difficult.

Filters allow shoppers to narrow down the search resultsso they can look at products in specific categories like kitchen appliances or cook books. However, only one generic filter can be applied at a time. Faceted navigation uses multiple filters at the same timewhich can be applied to specific product attributes.

Faceted search allows you to create filters based on keywords. You can provide shoppers with multiple filters, which makes the experience similar to one with faceted navigation, but faceted search provides more accurate results. This is also a smarter way to search as the search engine itself refines filters based on query results that are most likely to match with user intent. For one thing, faceted search prevents users from getting lost in your product catalog.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

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The longer answer is that you have to write that code yourself. What that means is that GraphQL won't let you write arbitrary queries out of the box. It will only support the types of queries defined in your GraphQL schema.

And finally write this query to get a list of firstName and lastName of all the users that match your search criteria:. For your use case it would look something like this:.

Queries and Mutations

Learn more. Asked 3 years, 9 months ago. Active 2 years, 5 months ago. Viewed 22k times. Example: What users have a first name starting with jason?

Jason Jason 3, 4 4 gold badges 29 29 silver badges 39 39 bronze badges. Active Oldest Votes. The short answer is: you don't. Note that users firstName: String : [User] with no exclamation mark after String can be used to make firstName optional.

Then you can program your server so that users returns all users while users firstName: "Max" returns only users whose first name is Max. Hope this helps someone down the line :. Mark Miller Mark Miller 4 4 silver badges 9 9 bronze badges. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog.

The Overflow How many jobs can be done at home? Socializing with co-workers while social distancing.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. The longer answer is that you have to write that code yourself.

What that means is that GraphQL won't let you write arbitrary queries out of the box. It will only support the types of queries defined in your GraphQL schema.

And finally write this query to get a list of firstName and lastName of all the users that match your search criteria:. For your use case it would look something like this:. Learn more. Asked 3 years, 9 months ago.

Active 2 years, 4 months ago. Viewed 22k times. Example: What users have a first name starting with jason? Jason Jason 3, 4 4 gold badges 29 29 silver badges 39 39 bronze badges. Active Oldest Votes. The short answer is: you don't. Note that users firstName: String : [User] with no exclamation mark after String can be used to make firstName optional.

Then you can program your server so that users returns all users while users firstName: "Max" returns only users whose first name is Max. Hope this helps someone down the line :.

Mark Miller Mark Miller 4 4 silver badges 9 9 bronze badges. Sign up or log in Sign up using Google.

graphql faceted search

Sign up using Facebook. Sign up using Email and Password. Post as a guest Name.Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since Elasticsearch belongs to "Search as a Service" category of the tech stack, while GraphQL can be primarily classified under "Query Languages". Elasticsearch and GraphQL are both open source tools.

Elasticsearch with Although we were using Elasticsearch in the beginning to power our in-app search, we moved this part of our processing over to Algolia a couple of months ago; this has proven to be a fantastic choice, letting us build search-related features with more confidence and speed.

Elasticsearch is only used for searching in internal tooling nowadays; hosting and running it reliably has been a task that took up too much time for us in the past and fine-tuning the results to reach a great user-experience was also never an easy task for us. With Algolia we can flexibly change ranking methods on the fly and can instead focus our time on fine-tuning the experience within our app. Memcached is used in front of most of the API endpoints to cache responses in order to speed up response times and reduce server-costs on our side.

We are starting to build one shirt data logic, structure and as an online clothing store we believe good ux and ui is a goal to drive a lot of click through. The problem is, how do we fetch data and how do we abstract the gap between the Front-end devs and backend-devs as we are just two in the technical unit.

We decided to go for GraphQL as our application-layer tool and Prisma for our database-layer abstracter. GraphQL comes with a bunch of real-time functionality in form of. Writing revolvers can be fun, but imagine writing revolvers nested deep down, curry braces flying around.

This is sure a welcome note to bugs and as a small team we need to focus more on what that matters more. Prisma generates this necessary CRUD resolves, mutations and subscription out of the box. We don't really have much budget at the moment so we are going to run our logic in a scalable cheap and cost effective cloud environment.

It's AWS Lambda and deploying our schema to Lambda is our best bet to minimize cost and same time scale. We are still at development stage and I believe, working on this start up will increase my dev knowledge. Off for Lunch :. Back inI was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. I had inherited years and years of technical debt and I knew things had to change radically.

For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. I came to know about Faceted Search and Lucene search and getting confusion regarding the same. Any one please give an idea regarding the difference between Faceted Search and Lucene search ,which scenario can apply both serach.

Faceted search is a kind of search provided by Lucene that searches through a particular dataset. They also provide 'normal' query searching, that searches through all the documents without bias and provides results. Faceted Search with Solr. Faceted Search - User's Guide. Faceted search is the dynamic clustering of items or search results into categories that let users drill into search results or even skip searching entirely by any value in any field.

Each facet displayed also shows the number of hits within the search that match that category. Also, check out these examples that are provided by the lucene devs. If you want to go in-depth into lucene architecture or even as a reference, this is a good paper - Architecture and Implementation of Apache Lucene.

See the search section ie. Here is a bit more concept about Lucene's Index Searching. Lucene is able to achieve fast search responses because, instead of searching the text directly, it searches an index instead. This would be the equivalent of retrieving pages in a book related to a keyword by searching the index at the back of a book, as opposed to searching the words in each page of the book. Generally Lucene supplies components to search inside the index and to obtain hits on the searched query.

QueryParser and indexSearcher are the main components involved in most Lucene based search engines. After the Index have been constructed with postings liststhe search application will retrieve the user query in the index. It first analyzes the user query using the same analyzer as in the indexing process, then transform the user query in to a Query object with respect to the Lucene query language.

Learn more. Difference between Faceted Search and Lucene search? Asked 3 years, 1 month ago. Active 3 years, 1 month ago. Viewed 2k times. Thanks in advance.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information.

I came to know about Faceted Search and Lucene search and getting confusion regarding the same. Any one please give an idea regarding the difference between Faceted Search and Lucene search ,which scenario can apply both serach.

Faceted search is a kind of search provided by Lucene that searches through a particular dataset. They also provide 'normal' query searching, that searches through all the documents without bias and provides results.

Faceted Search with Solr. Faceted Search - User's Guide. Faceted search is the dynamic clustering of items or search results into categories that let users drill into search results or even skip searching entirely by any value in any field.

Each facet displayed also shows the number of hits within the search that match that category. Also, check out these examples that are provided by the lucene devs. If you want to go in-depth into lucene architecture or even as a reference, this is a good paper - Architecture and Implementation of Apache Lucene. See the search section ie. Here is a bit more concept about Lucene's Index Searching.

Lucene is able to achieve fast search responses because, instead of searching the text directly, it searches an index instead. This would be the equivalent of retrieving pages in a book related to a keyword by searching the index at the back of a book, as opposed to searching the words in each page of the book.

Generally Lucene supplies components to search inside the index and to obtain hits on the searched query. QueryParser and indexSearcher are the main components involved in most Lucene based search engines. After the Index have been constructed with postings liststhe search application will retrieve the user query in the index.

It first analyzes the user query using the same analyzer as in the indexing process, then transform the user query in to a Query object with respect to the Lucene query language.

Learn more.

Using TopBraid Tagger and AutoClassifier to Support Faceted Search over Distributed Content

Difference between Faceted Search and Lucene search? Asked 3 years, 1 month ago. Active 3 years, 1 month ago. Viewed 2k times.

graphql faceted search

Thanks in advance. Jamsheer Jamsheer 2, 3 3 gold badges 19 19 silver badges 47 47 bronze badges. Active Oldest Votes. Two good posts that explain faceted search well - Faceted Search with Solr Faceted Search - User's Guide Faceted search is the dynamic clustering of items or search results into categories that let users drill into search results or even skip searching entirely by any value in any field.

Here is a bit more concept about Lucene's Index Searching - Lucene is able to achieve fast search responses because, instead of searching the text directly, it searches an index instead.

Sahil Agarwal Sahil Agarwal 2 2 silver badges 11 11 bronze badges. The Overflow Blog. The Overflow How many jobs can be done at home? Socializing with co-workers while social distancing. Featured on Meta. Community and Moderator guidelines for escalating issues via new response….

Feedback on Q2 Community Roadmap. Triage needs to be fixed urgently, and users need to be notified upon….The search will be available under a new route and implemented in a new React component. Again, this is a pretty standard setup. For the user to be able to comfortably navigate to the search functionality, you should also add a new navigation item to the Header. You can now navigate to the search feature using the new button in the Header :.

However, this time it takes in an argument called filter that will be used to constrain the list of links you want to retrieve. In this case, two where conditions are specified: A link is only returned if either its url contains the provided filter or its description contains the provided filter.

Perfect, the query is defined! But this time we actually want to load the data every time the user hits the search -button - not upon the initial load of the component.

This function injects the ApolloClient instance that you created in index. This client has a method called query which you can use to send a query manually instead of using the graphql higher-order component.

The implementation is almost trivial. Then type a search string into the text field, click the search -button and verify the links that are returned fit the filter conditions. GraphQL Fundamentals. Core Concepts. Big Picture Architecture.

GraphQL Search (ARTEM SHTATNOV - Software Engineer at Netflix)

Getting Started. Queries: Loading Links. Mutations: Creating Links. More Mutations and Updating the Store. Filtering: Searching the List of Links. How to GraphQL.

Advanced GraphQL. More GraphQL Concepts. Tooling and Ecosystem. Common Questions. All Frontend Tutorials.

graphql faceted search

All Backend Tutorials. Preparing the React components The search will be available under a new route and implemented in a new React component. Unlock the next chapter. What's the purpose of the 'withApollo' function? Edit on Github.


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