Resource-efficient way to obtain list of all Wikidata items with labels, altLabels and Description? - wikidata

Question

I want to check if string s is contained in any wikidata item's label, altLabel or description and if so, return all of them. The sheer number of Wikidata items prohibits the use of SPARQL, because it will reach a timeout, so I need to do it locally. I did the same for properties before by performing this query and parsing the result locally:
SELECT ?property ?propertyLabel ?propertyDescription (GROUP_CONCAT(DISTINCT(?altLabel); separator = ", ") AS ?altLabel_list) WHERE {
?property a wikibase:Property .
OPTIONAL { ?property skos:altLabel ?altLabel . FILTER (lang(?altLabel) = "en") }
SERVICE wikibase:label { bd:serviceParam wikibase:language "en" .}
}
GROUP BY ?property ?propertyLabel ?propertyDescription
It produces a table that looks similar to this "official" one on wikidata.
What is a space- (and ideally time-)efficient way of obtaining a list/table of all wikidata items with labels, descriptions and altLabels just like the one above? Namely, can I somehow avoid downloading the whole Wikidata dump, parsing it and building the list myself with standard hardware?
I found this tool, but am not sure if is capable of doing what I need. I do not want to waste community resources either.

Answer 1

The wdumps tool works and would seem to be the closest to what you're asking for, i. e. a complete list. If you look at the list of recent runs of the tool, you may find what you need anyway, because it's a common ask.
Aside from working with the whole list locally, the documentation recommends the SPARQL interface to wikipedia's "regular" search engine, like this:
SELECT ?item ?label
WHERE
{
SERVICE wikibase:mwapi
{
bd:serviceParam wikibase:endpoint "www.wikidata.org";
wikibase:api "Generator";
mwapi:generator "search";
mwapi:gsrsearch "inlabel:Frankfurt";
mwapi:gsrlimit "max".
?item wikibase:apiOutputItem mwapi:title.
}
?item rdfs:label ?label.
FILTER CONTAINS(?label, "Frankfurt")
}
And, as a third possibility, I want to mention the interface at https://query.wikidata.org/bigdata/ldf. This is a little-known API for the data. Judging by its speed and from its documentation, it is very efficient. But, as the linked example query shows, there are half a billion labels, so even a fast method of access such as this will be a challenge.