geohash | geohash for golang -

From the Firestore documentation on query limitations:

In a compound query, range (<, <=, >, >=) and not equals (!=, not-in) comparisons must all filter on the same field.

The way the inequality operators are implemented requires that you order on that field first. For the equality operator Firestore is able to do more on its own, for example combining information from multiple indexes in a so-called zig-zag-merge-join.

Security rules work on a document-level. Your code is trying to update the replies array in the users document, which is not allowed by any of your rules.

The match /replies in your rules applies to a replies subcollection under the users document. It has no effect on fields in the users document.

If you want the owner to update their entire document, and other signed in users to only update the replies field, you'll have to allow that in the rule on users.

Something like this:

1. Try reducing the data size on both sides of the join operator, by filtering out irrelevant or ill formatted rows and columns. Perhaps you can use geo_point_in_polygon\circle() to throw out irrelevant data.

2. Try using broadcast join or maybe shuffle join: https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/broadcastjoin https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/shufflequery

3. You can use s2\geohash\h3 hashing functions in two ways:

   a. Per each table, combine nearby points into one representative point. The idea is to use hash cell central point as a representative for all points that reside in the cell. This will reduce tables sizes. Something like:

Let's break down the problem as below:

1. Save geohash for each client document

Assume that we have clients collection with documents as below:

This query will never return any results:

Looks like geohash-java supports this:

An implementation of Geohashes in pure Java. The produced hashes, when using character precision (multiples of 5 bits) are compatible to the reference implementation geohash.org.

You can however also encode Geohashes down to the full available precision of a long i.e. 64 bits.

You can add the following to your pom.xml file if you are using Maven:

given length 4 geohash it will return length 5 geohash list

This is pretty straightforward - each letter in geohash encodes 5-bit (32 potential values) of the quad-tree. All 32 values are possible and represent different areas inside parent geohash rectangle, so if you want to get list of all the possible longer geohash values, just append these letters.

The list of 32 digits and letters used by geohash can be found in Wikipedia or any geohash implementation: "0123456789bcdefghjkmnpqrstuvwxyz". Just append each of these to shorter geohash, and you'll get all the possible longer ones.

frm probably does not have the correct crs to be show on the folium map.

Even if creating a GeoDataFrame with the crs parameter it seems to not change the original crs.

Addition of geohashes means that there is a new type for this kind of data. If you are using existing types for weather data, there will be no change in performance. There are internal improvements which make working with the geohash type more efficient than storing these values as strings of symbols, for example.

For more info, see the geohash documentation at https://questdb.io/docs/concept/geohashes/