I'm trying to figure out what's the best solution to find all nodes of certain types around a given GPS-Location.
Let's say I want to get all cafes, pubs, restaurant and parks around a given point X.xx,Y.yy.
[out:json];(node[amenity][leisure](around:500,52.2740711,10.5222147););out;
This returns nothing because I think it searches for nodes that are both, amenity and leisure which is not possible.
[out:json];(node[amenity or leisure](around:500,52.2740711,10.5222147););out;
[out:json];(node[amenity,leisure](around:500,52.2740711,10.5222147););out;
[out:json];(node[amenity;leisure](around:500,52.2740711,10.5222147););out;
[out:json];(node[amenity|leisure](around:500,52.2740711,10.5222147););out;
[out:json];(node[amenity]|[leisure](around:500,52.2740711,10.5222147););out;
[out:json];(node[amenity],[leisure](around:500,52.2740711,10.5222147););out;
[out:json];(node[amenity];[leisure](around:500,52.2740711,10.5222147););out;
These solutions result in an error (400: Bad Request)
The only working solution I found is the following one which results in really long queries
[out:json];(node[amenity=cafe](around:500,52.2740711,10.5222147);node[leisure=park](around:500,52.2740711,10.5222147);node[amenity=pub](around:500,52.2740711,10.5222147);node[amenity=restaurant](around:500,52.2740711,10.5222147););out;
Isn't there an easier solution without multiple "around" statements?
EDIT:
Found This on which is a little bit shorter. But still multiple "around" statements.
[out:json];(node["leisure"~"park"](around:400,52.2784715,10.5249662);node["amenity"~"cafe|pub|restaurant"](around:400,52.2784715,10.5249662););out;
What you're probably looking for is regular expression support for keys (not only values).
Here's an example based on your query above:
[out:json];
node[~"^(amenity|leisure)$"~"."](around:500,52.2740711,10.5222147);
out;
NB: Since version 0.7.54 (released in Q1/2017) Overpass API also supports filter criteria with 'or' conditions. See this example on how to use this new (if: ) filter.
Related
In an HTML document I have a large inline SVG object with groups bearing a variety of IDs (or none at all). I want to find all groups other than those whose IDs start with the letter sequences l0pzlo, l1pzloand l2pzlo. The task of finding just those IDs is easy
element.querySelectorAll("[id^=l0pzlo_],[id^=l1pzlo_],[id^=l2pzlo_]")
does the trick. However, I cannot work out how to get only those elements whose IDs DO NOT start with any of the three prefixes given above. I have attempted to use :notin a variety of different ways, e.g.
element.querySelectorAll(:not('[(id^=l0pzlo)]'))";
but nothing seems to be to the liking of the browser. How can I do this?
I think it would be more useful to leave my own answer here rather than just delete the question
element.querySelectorAll('*:not([id^=l0pzlo]):not([id^=l1pzlo]):not([id^=l2pzlo])');
works. Think of it as going about the task of filtering in a non-greedy way. First you get absolutely everything and then progressively filter out what you don't need with a sequence of one or more :nots
I have a query which returns a number of ways. I want to find nodes matching certain criteria which appear within those ways. Note that the nodes I'm interested in do not form part of the way itself, but do appear within the bounds of the way. Also, the ways do not all have corresponding areas, so using the area search doesn't work in all cases.
I've got a minimal example which finds way 95677318, and I want to be able to find node 1552949334:
(
way({{bbox}})["man_made"="lighthouse"];
)->.searchArea;
/*doesn't work:*/
/*node(area.searchArea)["seamark:name"];*/
/*recur down and find node directly, just for the purpose of this question*/
(
.searchArea;>;
node({{bbox}})["seamark:name"];
);
out;
(Try it on https://overpass-turbo.eu/s/EpV)
This feature is not yet available as of release 0.7.55. In case there's no corresponding area available on the Overpass server, this kind of query is simply not feasible.
See https://github.com/drolbr/Overpass-API/issues/77 for details.
I try to download the state borders of France (a few dozen states, not big data). Indeed I look for borders I can upload in my postgres database to localize POIs. OpenstreetMap seemed to be the good data source so I have tried to learn Overpass QL but it seems harder than I thought to do so... After some wiki reading I came to this:
way["name:en"="France"];
way["type"="boundary"];
way["boundary"="administrative"];
way["admin_level"="4"];
But the query endless runs... I am not sure about the query I made, is this the good syntax ? Thanks
There are several issues with your query:
Administrative boundaries are frequently modeled as relations, rather than ways in OSM. So querying for ways way[...] will not return the result you're looking for.
To fetch elements which have have several tags, you need to combine them like [key1=value1][key2=value2]. You current query would query ALL ways WORLDWIDE with type=boundary and then again WORLDWIDE all ways with admin_level=4. Obviously this is both very expensive and not what you're looking for.
out statement is mandatory to return some result. In your case, the query would in fact run, but it would never return anything.
My recommendation is to use the following query instead:
rel["ISO3166-2"~"^FR"]
[admin_level=4]
[type=boundary]
[boundary=administrative];
out geom;
Try it in overpass turbo: http://overpass-turbo.eu/s/lnv
I use Facebook and Google maps to get a full Geo Entities data values (country, city, street, zip...).
I store these values on my mongoDB,
I noticed that some locations are deffer in the way they were written on Face and on Google, for (an unreal) example Face wrote the name of 'Hawaii' with an 'e' - Haweii.
I use match_all fields (country + city + street...) to search for entities at the same location but since some are written a bit different i will not find them.
Is there a way make elasticsearch search for 'Hawaii' and any other option that sounds like Hawaii but written a bit different?
Thanks for any help!
Using Google API one can get a location's
full details
To match words that sound similar you can use the phonetic analyzer. You can also give fuzzy query a try to match words with spelling mistakes. None of them are fool proof though and may result in false positives. Guess you'll have to experiment a little to come up with a solution that best fits your need.
If you have a known set of differences between Facebook and Google maps, you could look at using Synonyms at either index time or query time to accommodate differences in the APIs; There are merits to taking either approach.
Looking for advice on handling ampersands and the word "and" in Lucene queries. My test queries are (including quotes):
"oil and gas field" (complete phrase)
"research and development" (complete phrase)
"r&d" (complete phrase)
Ideally, I'd like to use the QueryParser as the input is coming from the user.
During testing and doc reading, I found that using the StandardAnalyzer doesn't work for what I want. For the first two queries, a QueryParser.Parse converts them to:
contents:"oil gas field"
contents:"research development"
Which isn't what I want. If I use a PhraseQuery instead, I get no results (presumably because "and" isn't indexed.
If I use a SimpleAnalyzer, then I can find the phrases but QueryParser.Parse converts the last term to:
contents:"r d"
Which again, isn't quite what I'm looking for.
Any advice?
if you want to search for "and" you have to index it. Write you own Analyzer or remove "and" from the list of stop words. The same applies to the "r&d". Write your own Analyzer that creates 3 words from the text: "r", "d", "r&d".
Step one of working with Lucene is to accept that pretty much all of the work is done at the time of indexing. If you want to search for something then you index it. If you want to ignore something then you don't index it. It is this that allows Lucene to provide such high speed searching.
The upshot of this is that for an index to work effectively you have to anticipate what your analyzer needs to do up front. In this case I would write my own analyzer that doesn't strip any stop words and also transforms & to 'and' (and optionally # to 'at' etc). In the case of r&d matching research & development you are almost certainly going to have to implement some domain specific logic.
There are other ways of dealing with this. If you can differentiate between phrase searches and normal keyword searches then there is no reason you can't maintain two or more indexes to handle different types of search. This gives very quick searching but will require some more maintenance.
Another option is to use the high speed of Lucene to filter your initial results down to something more manageable using an analyzer that doesn't give false negatives. You can then run some detailed filtering over the full text of those documents that it does find to match the correct phrases.
Ultimately I think you are going to find that Lucene sacrifices accuracy in more advanced searches in order to provide speed, it is generally good enough for most people. You are probably in uncharted waters trying to tweak your analyzer this much.