Is it possible to conduct multiple spatial queries within the same SOLR (3.1+) request?
We currently have a need to allow user to search for inventory with a location of their choice via a frontend search form. But we want to also add another spatial search behind the scenes so it will include more inventory. The resulting search would result in a venn diagram type of search.
Edit 10.4.2011
Example construct: q=*:*&fq={!geofilt}&sfield=Location&(ClientId:"client1"&pt=40.68063802521456,-74.00390625&d=80.4672)%20OR%20_query_:(ClientId:"client2"&pt=36.1146460,-115.1728160&d=80.4672)
The above construct does not work, but hopefully demonstrates what I am trying to accomplish.
This is old, but it doesn't seem like it ever got a full answer. I had the same issue and found that this syntax works:
q =*:*& fq = (({
!geofilt sfield = Location pt = 40.68063802521456,
-74.00390625 d = 80.4672
}
AND ClientId : "client1")OR({
!geofilt sfield = Location pt = 36.1146460,
-115.1728160 d = 80.4672
}
AND ClientId : "client2"))
It looks like, you like to run N querys in one request in order to get one result set per query?!
So Field Collapsing ( http://wiki.apache.org/solr/FieldCollapsing ) is what you are looking for. Unfortunately FieldCollapsing is only available from 3.3.
Depending on your needs, maybe counted results from different faceted searches could be also useful?!
What if you moved your second location query into an additional filter query, like below:
q=*:*&fq={!geofilt}&sfield=Location&(ClientId:"client1"&pt=40.68063802521456,-74.00390625&d=80.4672)&fq={!geofilt}&sfield=Location&(ClientId:"client2"&pt=36.1146460,-115.1728160&d=80.4672)
Will that provide the results that you are looking for? It might end up being too limiting, but thought it was worth trying.
You might also try:
q=*:*&fq={!geofilt}&sfield=Location&((ClientId:"client1"&pt=40.68063802521456,-74.00390625&d=80.4672)%20OR%20(ClientId:"client2"&pt=36.1146460,-115.1728160&d=80.4672))
Related
I'm a newbie to Django as well as neo4j. I'm using Django 1.4.5, neo4j 1.9.2 and neo4django 0.1.8
I've created NodeModel for a person node and indexed it on 'owner' and 'name' properties. Here is my models.py:
from neo4django.db import models as models2
class person_conns(models2.NodeModel):
owner = models2.StringProperty(max_length=30,indexed=True)
name = models2.StringProperty(max_length=30,indexed=True)
gender = models2.StringProperty(max_length=1)
parent = models2.Relationship('self',rel_type='parent_of',related_name='parents')
child = models2.Relationship('self',rel_type='child_of',related_name='children')
def __unicode__(self):
return self.name
Before I connected to Neo4j server, I set auto indexing to True and and gave indexable keys in conf/neo4j.properties file as follows:
# Autoindexing
# Enable auto-indexing for nodes, default is false
node_auto_indexing=true
# The node property keys to be auto-indexed, if enabled
node_keys_indexable=owner,name
# Enable auto-indexing for relationships, default is false
relationship_auto_indexing=true
# The relationship property keys to be auto-indexed, if enabled
relationship_keys_indexable=child_of,parent_of
I followed Neo4j: Step by Step to create an automatic index to update above file and manually create node_auto_index on neo4j server.
Below are the indexes created on neo4j server after executing syndb of django on neo4j database and manually creating auto indexes:
graph-person_conns lucene
{"to_lower_case":"true", "_blueprints:type":"MANUAL","type":"fulltext"}
node_auto_index lucene
{"_blueprints:type":"MANUAL", "type":"exact"}
As suggested in https://github.com/scholrly/neo4django/issues/123 I used connection.cypher(queries) to query the neo4j database
For Example:
listpar = connection.cypher("START no=node(*) RETURN no.owner?, no.name?",raw=True)
Above returns the owner and name of all nodes correctly. But when I try to query on indexed properties instead of 'number' or '*', as in case of:
listpar = connection.cypher("START no=node:node_auto_index(name='s2') RETURN no.owner?, no.name?",raw=True)
Above gives 0 rows.
listpar = connection.cypher("START no=node:graph-person_conns(name='s2') RETURN no.owner?, no.name?",raw=True)
Above gives
Exception Value:
Error [400]: Bad Request. Bad request syntax or unsupported method.
Invalid data sent: (' expected but-' found after graph
I tried other strings like name, person_conns instead of graph-person_conns but each time it gives error that the particular index does not exist. Am I doing a mistake while adding indexes?
My project mainly depends on filtering the nodes based on properties, so this part is really essential. Any pointers or suggestions would be appreciated. Thank you.
This is my first post on stackoverflow. So in case of any missing information or confusing statements please be patient. Thank you.
UPDATE:
Thank you for the help. For the benefit of others I would like to give example of how to use cypher queries to traverse/find shortest path between two nodes.
from neo4django.db import connection
results = connection.cypher("START source=node:`graph-person_conns`(person_name='s2sp1'),dest=node:`graph-person_conns`(person_name='s2c1') MATCH p=ShortestPath(source-[*]->dest) RETURN extract(i in nodes(p) : i.person_name), extract(j in rels(p) : type(j))")
This is to find shortest path between nodes named s2sp1 and s2c1 on the graph. Cypher queries are really cool and help traverse nodes limiting the hops, types of relations etc.
Can someone comment on the performance of this method? Also please suggest if there are any other efficient methods to access Neo4j from Django. Thank You :)
Hm, why are you using Cypher? neo4django QuerySets work just fine for the above if you set the properties to indexed=True (or not, it'll just be slower for those).
people = person_conns.objects.filter(name='n2')
The neo4django docs have some other querying examples, as do the Django docs. Neo4django executes those queries as Cypher on the backend- you really shouldn't need to drop down to writing the Cypher yourself unless you have a very particular traversal pattern or a performance issue.
Anyway, to more directly tackle your question- the last example you used needs backticks to escape the index name, like
listpar = connection.cypher("START no=node:`graph-person_conns`(name='s2') RETURN no.owner?, no.name?",raw=True)
The first example should work. One thought- did you flip the autoindexing on before or after saving the nodes you're searching for? If after, note that you'll have to manually reindex the nodes either using the Java API or by re-setting properties on the node, since it won't have been autoindexed.
HTH, and welcome to StackOverflow!
I executed some query like "Address:Jack*". It show numFound = 5214 and display 100 documents in results page(I changed default display results from 10 to 100).
How can I get all documents.
I remember myself doing &rows=2147483647
2,147,483,647 is integer's maximum value. I recall using a number bigger than that once and having a NumberFormatException because it couldn't be parsed into an int. I don't know if they use Long nowadays, but 2 billion rows is normally more than enough.
Small note:
Be careful if you are planning to do this in production. If you do a query like * : * and your index is big, you could transferring a couple of gigabytes in that query.
If you know you won't have many docs, go ahead and use integer's max value.
On the other hand, if you are doing a one-time script and just need to dump all results (for example document ID's) then this approach is valid, if you don't mind waiting 3-5 minutes for a query to return.
Don't use &rows=2147483647
Don't use Integer.MAX_VALUE(2147483647) as value of rows in production. This will heavily slow down your query even if you have a small resultset, because solr preallocates a queue in this size. see https://issues.apache.org/jira/browse/SOLR-7580
I strongly suggest to use Exporting Result Sets
It’s possible to export fully sorted result sets using a special rank query parser and response writer specifically designed to work together to handle scenarios that involve sorting and exporting millions of records.
Or I suggest to use Deep Paging.
Simple Pagination is a easy thing when you have few documents to read and all you have to do is play with start and rows parameters. But this is not a feasible way when you have many documents, I mean hundreds of thousands or even millions.
This is the kind of thing that could bring your Solr server to their knees.
For typical applications displaying search results to a human user,
this tends to not be much of an issue since most users don’t care
about drilling down past the first handful of pages of search results
— but for automated systems that want to crunch data about all of the
documents matching a query, it can be seriously prohibitive.
This means that if you have a website and are paging search results, a real user do not go so further but consider on the other hand what can happen if a spider or a scraper try to read all the website pages.
Now we are talking of Deep Paging.
I’ll suggest to read this amazing post:
https://lucidworks.com/post/coming-soon-to-solr-efficient-cursor-based-iteration-of-large-result-sets/
And take a look at this document page:
https://solr.apache.org/guide/pagination-of-results.html
And here is an example that try to explain how to paginate using the cursors.
SolrQuery solrQuery = new SolrQuery();
solrQuery.setRows(500);
solrQuery.setQuery("*:*");
solrQuery.addSort("id", ORDER.asc); // Pay attention to this line
String cursorMark = CursorMarkParams.CURSOR_MARK_START;
boolean done = false;
while (!done) {
solrQuery.set(CursorMarkParams.CURSOR_MARK_PARAM, cursorMark);
QueryResponse rsp = solrClient.query(solrQuery);
String nextCursorMark = rsp.getNextCursorMark();
for (SolrDocument d : rsp.getResults()) {
...
}
if (cursorMark.equals(nextCursorMark)) {
done = true;
}
cursorMark = nextCursorMark;
}
Returning all the results is never a good option as It would be very slow in performance.
Can you mention your use case ?
Also, Solr rows parameter helps you to tune the number of the results to be returned.
However, I don't think there is a way to tune rows to return all results. It doesn't take a -1 as value.
So you would need to set a high value for all the results to be returned.
What you should do is to first create a SolrQuery shown below and set the number of documents you want to fetch in a batch.
int lastResult=0; //this is for processing the future batch
String query = "id:[ lastResult TO *]"; // just considering id for the sake of simplicity
SolrQuery solrQuery = new SolrQuery(query).setRows(500); //setRows will set the required batch, you can change this to whatever size you want.
SolrDocumentList results = solrClient.query(solrQuery).getResults(); //execute this statement
Here I am considering an example of search by id, you can replace it with any of your parameter to search upon.
The "lastResult" is the variable you can change after execution of the first 500 records(500 is the batch size) and set it to the last id got from the results.
This will help you execute the next batch starting with last result from previous batch.
Hope this helps. Shoot up a comment below if you need any clarification.
For selecting all documents in dismax/edismax via Solarium php client, the normal query syntax : does not work. To select all documents set the default query value in solarium query to empty string. This is required as the default query in Solarium is :. Also set the alternative query to :. Dismax/eDismax normal query syntax does not support :, but the alternative query syntax does.
For more details following book can be referred
http://www.packtpub.com/apache-solr-php-integration/book
As the other answers pointed out, you can configure the rows to be max integer to yield back all the results for a query.
I would recommend though to use Solr feature of pagination, and build a function that will return for you all the results using the cursorMark API. The gist of it is you set the cursorMark parameter to '*', you set the page size(rows parameter), and on each result you'll get a cursorMark for the next page, so you execute the same query only with the cursorMark given from the last result. This way you'll have more flexibility on how much of the results you want back, in a much more performant way.
The way I dealt with the problem is by running the query twice:
// Start with your (usually small) default page size
solrQuery.setRows(50);
QueryResponse response = solrResponse(query);
if (response.getResults().getNumFound() > 50) {
solrQuery.setRows(response.getResults().getNumFound());
response = solrResponse(query);
}
It makes a call twice to Solr, but gets you all matching records....with the small performance penalty.
query.setRows(Integer.MAX_VALUE);
works for me!!
Yet another potentially embarrassing question. Please feel free to point any obvious solution that may have been overlooked - I have searched for solutions previously and found nothing, but sometimes it's a matter of choosing the wrong keywords to search for.
Here's the situation: coded my own RequestHandler a few months ago for an enterprise-y system, in order to inject a few necessary security parameters as an extra filter in all queries made to the solr core. Everything runs smoothly until the part where the docs resulting from a query to the index are collected and then returned to the user.
Basically after the filter is created and the query is executed we get a set of document ids (and scores), but then we have to iterate through the ids in order to build the result set, one hit at a time - which is a good 10x slower that querying the standard requesthandler, and only bound to get worse as the number of results increase. Even worse, since our schema heavily relies on dynamic fields for flexibility, there is no way (that I know of) of previously retrieving the list of fields to retrieve per document, other than testing all possible combinations per doc.
The code below is a simplified version of the one running in production, for querying the SolrIndexSearcher and building the response.
Without further ado, my questions are:
is there any way of retrieving all results at once, instead of building a response document by document?
is there any possibility of getting the list of fields on each result, instead of testing all possible combinations?
any particular WTFs in this code that I should be aware of? Feel free to kick me!
//function that queries index and handles results
private void searchCore(SolrIndexSearcher searcher, Query query,
Filter filter, int num, SolrDocumentList results) {
//Executes the query
TopDocs col = searcher.search(query,filter, num);
//results
ScoreDoc[] docs = col.scoreDocs;
//iterate & build documents
for (ScoreDoc hit : docs) {
Document doc = reader.document(hit.doc);
SolrDocument sdoc = new SolrDocument();
for(Object f : doc.getFields()) {
Field fd = ((Field) f);
//strings
if (fd.isStored() && (fd.stringValue() != null))
sdoc.addField(fd.name(), fd.stringValue());
else if(fd.isStored()) {
//Dynamic Longs
if (fd.name().matches(".*_l") ) {
ByteBuffer a = ByteBuffer.wrap(fd.getBinaryValue(),
fd.getBinaryOffset(), fd.getBinaryLength());
long testLong = a.getLong(0);
sdoc.addField(fd.name(), testLong );
}
//Dynamic Dates
else if(fd.name().matches(".*_dt")) {
ByteBuffer a = ByteBuffer.wrap(fd.getBinaryValue(),
fd.getBinaryOffset(), fd.getBinaryLength());
Date dt = new Date(a.getLong());
sdoc.addField(fd.name(), dt );
}
//...
}
}
results.add(sdoc);
}
}
Per OPs request:
Although this doesn't answer your specific question, I would suggest another option to solve your problem.
To add a Filter to all queries, you can add an "appends" section to the StandardRequestHandler in the SolrConfig.xml file. Add a "fl" (stands for filter) section and add your filter. Every request piped through the StandardRequestHandler will have the filter appended to it automatically.
This filter is treated like any other, so it is cached in the FilterCache. The result is fairly fast filtering (through docIds) at query time. This may allow you to avoid having to pull the individual documents in your solution to apply the filtering criteria.
Simple one really. In SQL, if I want to search a text field for a couple of characters, I can do:
SELECT blah FROM blah WHERE blah LIKE '%text%'
The documentation for App Engine makes no mention of how to achieve this, but surely it's a common enough problem?
BigTable, which is the database back end for App Engine, will scale to millions of records. Due to this, App Engine will not allow you to do any query that will result in a table scan, as performance would be dreadful for a well populated table.
In other words, every query must use an index. This is why you can only do =, > and < queries. (In fact you can also do != but the API does this using a a combination of > and < queries.) This is also why the development environment monitors all the queries you do and automatically adds any missing indexes to your index.yaml file.
There is no way to index for a LIKE query so it's simply not available.
Have a watch of this Google IO session for a much better and more detailed explanation of this.
i'm facing the same problem, but i found something on google app engine pages:
Tip: Query filters do not have an explicit way to match just part of a string value, but you can fake a prefix match using inequality filters:
db.GqlQuery("SELECT * FROM MyModel WHERE prop >= :1 AND prop < :2",
"abc",
u"abc" + u"\ufffd")
This matches every MyModel entity with a string property prop that begins with the characters abc. The unicode string u"\ufffd" represents the largest possible Unicode character. When the property values are sorted in an index, the values that fall in this range are all of the values that begin with the given prefix.
http://code.google.com/appengine/docs/python/datastore/queriesandindexes.html
maybe this could do the trick ;)
Altough App Engine does not support LIKE queries, have a look at the properties ListProperty and StringListProperty. When an equality test is done on these properties, the test will actually be applied on all list members, e.g., list_property = value tests if the value appears anywhere in the list.
Sometimes this feature might be used as a workaround to the lack of LIKE queries. For instance, it makes it possible to do simple text search, as described on this post.
You need to use search service to perform full text search queries similar to SQL LIKE.
Gaelyk provides domain specific language to perform more user friendly search queries. For example following snippet will find first ten books sorted from the latest ones with title containing fern
and the genre exactly matching thriller:
def documents = search.search {
select all from books
sort desc by published, SearchApiLimits.MINIMUM_DATE_VALUE
where title =~ 'fern'
and genre = 'thriller'
limit 10
}
Like is written as Groovy's match operator =~.
It supports functions such as distance(geopoint(lat, lon), location) as well.
App engine launched a general-purpose full text search service in version 1.7.0 that supports the datastore.
Details in the announcement.
More information on how to use this: https://cloud.google.com/appengine/training/fts_intro/lesson2
Have a look at Objectify here , it is like a Datastore access API. There is a FAQ with this question specifically, here is the answer
How do I do a like query (LIKE "foo%")
You can do something like a startWith, or endWith if you reverse the order when stored and searched. You do a range query with the starting value you want, and a value just above the one you want.
String start = "foo";
... = ofy.query(MyEntity.class).filter("field >=", start).filter("field <", start + "\uFFFD");
Just follow here:
init.py#354">http://code.google.com/p/googleappengine/source/browse/trunk/python/google/appengine/ext/search/init.py#354
It works!
class Article(search.SearchableModel):
text = db.TextProperty()
...
article = Article(text=...)
article.save()
To search the full text index, use the SearchableModel.all() method to get an
instance of SearchableModel.Query, which subclasses db.Query. Use its search()
method to provide a search query, in addition to any other filters or sort
orders, e.g.:
query = article.all().search('a search query').filter(...).order(...)
I tested this with GAE Datastore low-level Java API. Me and works perfectly
Query q = new Query(Directorio.class.getSimpleName());
Filter filterNombreGreater = new FilterPredicate("nombre", FilterOperator.GREATER_THAN_OR_EQUAL, query);
Filter filterNombreLess = new FilterPredicate("nombre", FilterOperator.LESS_THAN, query+"\uFFFD");
Filter filterNombre = CompositeFilterOperator.and(filterNombreGreater, filterNombreLess);
q.setFilter(filter);
In general, even though this is an old post, a way to produce a 'LIKE' or 'ILIKE' is to gather all results from a '>=' query, then loop results in python (or Java) for elements containing what you're looking for.
Let's say you want to filter users given a q='luigi'
users = []
qry = self.user_model.query(ndb.OR(self.user_model.name >= q.lower(),self.user_model.email >= q.lower(),self.user_model.username >= q.lower()))
for _qry in qry:
if q.lower() in _qry.name.lower() or q.lower() in _qry.email.lower() or q.lower() in _qry.username.lower():
users.append(_qry)
It is not possible to do a LIKE search on datastore app engine, how ever creating an Arraylist would do the trick if you need to search a word in a string.
#Index
public ArrayList<String> searchName;
and then to search in the index using objectify.
List<Profiles> list1 = ofy().load().type(Profiles.class).filter("searchName =",search).list();
and this will give you a list with all the items that contain the world you did on the search
If the LIKE '%text%' always compares to a word or a few (think permutations) and your data changes slowly (slowly means that it's not prohibitively expensive - both price-wise and performance-wise - to create and updates indexes) then Relation Index Entity (RIE) may be the answer.
Yes, you will have to build additional datastore entity and populate it appropriately. Yes, there are some constraints that you will have to play around (one is 5000 limit on the length of list property in GAE datastore). But the resulting searches are lightning fast.
For details see my RIE with Java and Ojbectify and RIE with Python posts.
"Like" is often uses as a poor-man's substitute for text search. For text search, it is possible to use Whoosh-AppEngine.
Simple one really. In SQL, if I want to search a text field for a couple of characters, I can do:
SELECT blah FROM blah WHERE blah LIKE '%text%'
The documentation for App Engine makes no mention of how to achieve this, but surely it's a common enough problem?
BigTable, which is the database back end for App Engine, will scale to millions of records. Due to this, App Engine will not allow you to do any query that will result in a table scan, as performance would be dreadful for a well populated table.
In other words, every query must use an index. This is why you can only do =, > and < queries. (In fact you can also do != but the API does this using a a combination of > and < queries.) This is also why the development environment monitors all the queries you do and automatically adds any missing indexes to your index.yaml file.
There is no way to index for a LIKE query so it's simply not available.
Have a watch of this Google IO session for a much better and more detailed explanation of this.
i'm facing the same problem, but i found something on google app engine pages:
Tip: Query filters do not have an explicit way to match just part of a string value, but you can fake a prefix match using inequality filters:
db.GqlQuery("SELECT * FROM MyModel WHERE prop >= :1 AND prop < :2",
"abc",
u"abc" + u"\ufffd")
This matches every MyModel entity with a string property prop that begins with the characters abc. The unicode string u"\ufffd" represents the largest possible Unicode character. When the property values are sorted in an index, the values that fall in this range are all of the values that begin with the given prefix.
http://code.google.com/appengine/docs/python/datastore/queriesandindexes.html
maybe this could do the trick ;)
Altough App Engine does not support LIKE queries, have a look at the properties ListProperty and StringListProperty. When an equality test is done on these properties, the test will actually be applied on all list members, e.g., list_property = value tests if the value appears anywhere in the list.
Sometimes this feature might be used as a workaround to the lack of LIKE queries. For instance, it makes it possible to do simple text search, as described on this post.
You need to use search service to perform full text search queries similar to SQL LIKE.
Gaelyk provides domain specific language to perform more user friendly search queries. For example following snippet will find first ten books sorted from the latest ones with title containing fern
and the genre exactly matching thriller:
def documents = search.search {
select all from books
sort desc by published, SearchApiLimits.MINIMUM_DATE_VALUE
where title =~ 'fern'
and genre = 'thriller'
limit 10
}
Like is written as Groovy's match operator =~.
It supports functions such as distance(geopoint(lat, lon), location) as well.
App engine launched a general-purpose full text search service in version 1.7.0 that supports the datastore.
Details in the announcement.
More information on how to use this: https://cloud.google.com/appengine/training/fts_intro/lesson2
Have a look at Objectify here , it is like a Datastore access API. There is a FAQ with this question specifically, here is the answer
How do I do a like query (LIKE "foo%")
You can do something like a startWith, or endWith if you reverse the order when stored and searched. You do a range query with the starting value you want, and a value just above the one you want.
String start = "foo";
... = ofy.query(MyEntity.class).filter("field >=", start).filter("field <", start + "\uFFFD");
Just follow here:
init.py#354">http://code.google.com/p/googleappengine/source/browse/trunk/python/google/appengine/ext/search/init.py#354
It works!
class Article(search.SearchableModel):
text = db.TextProperty()
...
article = Article(text=...)
article.save()
To search the full text index, use the SearchableModel.all() method to get an
instance of SearchableModel.Query, which subclasses db.Query. Use its search()
method to provide a search query, in addition to any other filters or sort
orders, e.g.:
query = article.all().search('a search query').filter(...).order(...)
I tested this with GAE Datastore low-level Java API. Me and works perfectly
Query q = new Query(Directorio.class.getSimpleName());
Filter filterNombreGreater = new FilterPredicate("nombre", FilterOperator.GREATER_THAN_OR_EQUAL, query);
Filter filterNombreLess = new FilterPredicate("nombre", FilterOperator.LESS_THAN, query+"\uFFFD");
Filter filterNombre = CompositeFilterOperator.and(filterNombreGreater, filterNombreLess);
q.setFilter(filter);
In general, even though this is an old post, a way to produce a 'LIKE' or 'ILIKE' is to gather all results from a '>=' query, then loop results in python (or Java) for elements containing what you're looking for.
Let's say you want to filter users given a q='luigi'
users = []
qry = self.user_model.query(ndb.OR(self.user_model.name >= q.lower(),self.user_model.email >= q.lower(),self.user_model.username >= q.lower()))
for _qry in qry:
if q.lower() in _qry.name.lower() or q.lower() in _qry.email.lower() or q.lower() in _qry.username.lower():
users.append(_qry)
It is not possible to do a LIKE search on datastore app engine, how ever creating an Arraylist would do the trick if you need to search a word in a string.
#Index
public ArrayList<String> searchName;
and then to search in the index using objectify.
List<Profiles> list1 = ofy().load().type(Profiles.class).filter("searchName =",search).list();
and this will give you a list with all the items that contain the world you did on the search
If the LIKE '%text%' always compares to a word or a few (think permutations) and your data changes slowly (slowly means that it's not prohibitively expensive - both price-wise and performance-wise - to create and updates indexes) then Relation Index Entity (RIE) may be the answer.
Yes, you will have to build additional datastore entity and populate it appropriately. Yes, there are some constraints that you will have to play around (one is 5000 limit on the length of list property in GAE datastore). But the resulting searches are lightning fast.
For details see my RIE with Java and Ojbectify and RIE with Python posts.
"Like" is often uses as a poor-man's substitute for text search. For text search, it is possible to use Whoosh-AppEngine.