Apache Solr Jobs

5 were found based on your criteria {{ paging.total|number:0 }} were found based on your criteria

show all
  • Hourly ({{ jobTypeController.getFacetCount("0")|number:0}})
  • Fixed Price ({{ jobTypeController.getFacetCount("1")|number:0}})
Fixed-Price - Intermediate ($$) - Est. Budget: $1,750 - Posted
We are a fast growing company currently having a project that is in the latter stages of development and need a competent developer to implement changes to a existing website from design to technical. We are looking to make a directory software with search functionality. Knowing Solr or ElasticSearch is a plus in winning this job. We have more details for the right candidate who will be shortlisted. Please reply back with "RoR expert" to be considered for this position. Everyone else will be ignored. Please share your 5 most advanced projects in RoR that you have made. Outline the advanced features about each one. Happy Bidding
  • Number of freelancers needed: 2
Skills: Apache Solr API Development Elasticsearch Ruby
Fixed-Price - Intermediate ($$) - Est. Budget: $200 - Posted
Here is what I am looking for: I currently have a MySQL database table with about 7 fields including one with all data from the other 6 fields. I run a query like this: SELECT * FROM data WHERE MATCH (alldata) AGAINST('$keywords' IN BOOLEAN MODE) ORDER BY MATCH(alldata) AGAINST('$keywords' IN BOOLEAN MODE) DESC LIMIT 25; $keywords variable is all keywords, some required and some not (but if found higher score) It works ok but it is quite slow and it bogging down my MySQL server, even with indexing. So I am looking to use ElasticSearch or Solr or something to do the same thing only much faster and maybe better matching. I don't really care what system is used but it should work with PHP. I'm open to suggestions. Explain to me why I should use your solution. Here is what it needs to do: 1. I am looking to replace the MySQL database with a better matching/searching system. I've looked at ElasticSearch and Solr and both look good but I don't have any experience with them. 2. I would like to just use an include to use it with my current script. ex. $results = db_matches($keywords); 3. I can setup the keywords variable to whatever format is needed. But it will be some required but the more matches rank highest. 4. It would return up to top 25 matches. 5. It would match it with the alldata field. 6. The database will have 6 or so fields which would be returned in the results. 7. The database will have 2 million+ rows (From what I've read ES and Solr are a bit different in their storage system but I'm using rows to explain how much data). 8. It should be a fast search. I would think definitely under a second but the faster the better. 9. I have a fairly good VPS. 10. You would setup whatever system is used on my server. Hopefully that explains it fairly well. If you have any questions let me know. I'm hoping it won't be too big of a job. It seems fairly simple to someone who has worked with these database systems before. Experience is a plus. If you have experience please put in a bid.
Skills: Apache Solr Elasticsearch
Fixed-Price - Expert ($$$) - Est. Budget: $1,000 - Posted
The job will involve: - Modifying an Open Source software to turn it into a fully operational web-based software. - Building data analytics and visualization tools Essential skills: SPARQL, RDF, OWL, understanding ontology Javascript, XML, HTML, CSS, MySQL, Elastic Search, Apache Solr, Apache TomCat, Linux
Skills: Apache Solr Apache Ant Apache Tomcat CSS
Fixed-Price - Expert ($$$) - Est. Budget: $2,000 - Posted
I need to perform several lucene queries on a column of text within a CSV. The output must include a binary output that indicates if the text within a cell contains or does not contain each lucene search string. Ideally, I would like to be able to replicate this process in the future for non-technical analysts. For this reason, I believe a connection between Solr and Rapidminer would be a user friendly option, but I am open to other methods for executing this. Thank you very much! An example of the tags is here: https://app.box.com/shared/static/brchu4y7tmdtszvr2xxcdqqopsjewuou.xlsx An example of the data is here (and attached): https://app.box.com/shared/static/yy21h8t4gkfihx5hy0su8ng1h7y4f24e.csv
Skills: Apache Solr Elasticsearch Lucene Search Rapid Miner
Fixed-Price - Expert ($$$) - Est. Budget: $1,000 - Posted
Hello All, We are building a application for matching professionals with job Postings and jobs with professionals. For this we need matching enigne which can do clustering, indexing, Searching, matching, and then providing recommendations based on match score. When job seeker logs into application he should get job recommendation based on his profile without entring any search query and when recruiter logs in he should get candidates recommendations based on jobs he posted. We need to do matching in real time as the user logs in we have to find all matching jobs to his profile.We use sqlite database and we intended to use Elasticsearch or Solr to build this recommendaton/search engine. Your solution should be highly scalable, robust ,accurate and should work for variety of job types and resumes like any other job portal like Careerbuilder,linkedin or monster. Information we are collecting is : (Stored in SQLite) Data is highly structured and you wont have to work much on data preparation. JOB POSTING 1. Skills required for job. - This is array of skills. ex. Java, php,html,python,sql 2. Total years of experience required for job 3. Job description - Text paragraph (Need parsing to find token to boost search) 4. Desired Qualification - Tex Paragraph (Need parsing to find token to boost search) 5. Education qualification required (Low importance) 6. Job function (Low importance) (There are other paramters too like job location,salary. Those can be used to boost search and matching score. CANDIDATE PROFILE 1. Overall Skills -This is array of skills. ex. Java, php,html,python,sql 2. Total years of experience of candidate 3. Past experiences Experience 1 - No of years in this position (months) Skills used array - ex. Java, php,html,python,sql Job responsibilities: Text paragraph about job responsibilities Experience 2 - No of years in this position (months) Skills used array - ex. Java, php,html,python,sql Job responsibilities: Text paragraph about job responsibilities Experience 3 - No of years in this position (months) Skills used array - ex. Java, php,html,python,sql Job responsibilities: Text paragraph about job responsibilities and so on.. 4. Education qualification of candidates (Low importance) 5. Job function (Low importance) Based on information collected above we want you to build algorithm to recommend jobs to candidates and candidates to jobs.We are using PHP for our application so code in PHP is preferred but not necessary. We proposes Elasticsearch/Solr for clustering, matching and providing recommendations. Elasticsearch/Solr will be deployed outside our ready application. We can keep data in Sqlite database, but data has to be ingested in Elasticsearch/Solr in realtime in order to Elasticsearh/Solr can build an inverted index, make clusterization and perform faster search. Ready application will deal with Elasticsearch/Solr by means of HTTP requests, fetching recommendations and showing them to a user. Elasticsearch/Solr Should provide content-based and behaviour based,like this recomendations. The final solution will consist of: - set of code modules, scripts and instructions for Solr deployment and configuration; - client library with examples of making search/recommendation requests - documentation, describing applied algorithms,methods - Generate random set of jobs/seekers - Setup Elasticsearch/Solr, create schema, ingest data - Attribute-based (matching by job title, skills, years of experience, location) - Hierarchical Classification (requires hierarchical classification of job/industries) - More-like-this (matching by job description, previous experience) - Concept-Based (recommending concepts (clusters)) - Collaborative filtering (recommending jobs "liked/applied" by similar users) In future we may have similar work. So consider this as long term opportunity. Don't bid if you don't have background in Elasticsearch/Solr/Search-Information retrieval/machine learning or you haven't done similar kind of work before...
Skills: Apache Solr Elasticsearch Lucene Search Machine learning