Slow geo query

## Describe Development Experience Issue:

Hi, so I've noticed that spatial querying is extremely slow on my machine and was wondering if that's normal for Influx or am I'm doing something wrong.

I have a [dataset of ships' positions from NOAA](https://coast.noaa.gov/htdata/CMSP/AISDataHandler/2020/index.html), one day of which I downloaded and saved in InfluxDB.

Unfortunately when querying the data I get results after extremely long time. I'd want to query data at `level=24` and time range of 24h, but as things are now it takes 72s to query ships within a bounding box and a time range of 1 minute.

### Steps to reproduce:

1. Install InfluxDB 2.7.6 from Docker
2. Download [ships' positions from one day](https://coast.noaa.gov/htdata/CMSP/AISDataHandler/2020/index.html)
3. Write them to influx using python `InfluxDBClient`:
```python
write_api.write(bucket=bucket_name, org=organization_id,
record=df,
data_frame_measurement_name="vessels_ais_31_12",
data_frame_tag_columns=data_frame_tag_columns,
data_frame_timestamp_column="BaseDateTime",
)
```
4. Create a new bucket with just spatial index and basic information:
```python
level = 24
for start, end in generate_time_ranges_for_day(day, interval):
flux_query = f"""
import "experimental/geo"

from(bucket: "{raw_data_bucket}")
|> range(start: {start}, stop: {end})
|> filter(fn: (r) => r._measurement == "vessels_ais_31_12")
|> filter(fn: (r) => r._field == "LAT" or r._field == "LON")
|> geo.shapeData(latField: "{lat_field_name}", lonField: "{lon_field_name}", level: {level})
|> to
(bucket: "{indexed_data_bucket}", tagColumns: ["s2_cell_id", "MMSI"], fieldFn: (r) => ({{"lat": r.lat, "lon": r.lon}}))
"""
```
5. Query the data:
```python
region = {{
minLat: {min_lat},
maxLat: {max_lat},
minLon: {min_lon},
maxLon: {max_lon},
}}

from(bucket: "{bucket}")
|> range(start: {start_date}, stop: {stop_date})
|> filter(fn: (r) => r._measurement == "vessels_ais_31_12")
|> geo.filterRows(region: region, level: {level}, strict: {strict})
"""
```

### Desired result:

## Ideal

Returns result from **24h period** on **level 24** in less than 10 seconds.

## Less ideal

Returns ideal result in less than 10 minutes.

### Actual result:

Range of just **one minute**

On 5GB memory:
Lvl 10 - 72s
Lvl 11 - 122s
Lvl 12 - 113s
Lvl 13 - 134s
Lvl 14 - 122s
Lvl 15 - 139s
Lvl 16 - 222s
Lvl 17 - 573s
Lvl 18 - timeout after 600 seconds

On 16GB memory:
Lvl 10 - 109s
Lvl 11 - 109s
Lvl 12 - 104s
Lvl 13 - 105s
Lvl 14 - 110s
Lvl 15 - 131s
Lvl 16 - 220s
Lvl 17 - 536s
Lvl 18 - timeout after 600 seconds

## Hardware Environment:

- Package: laptop, localhost, setup on docker. I used `influx:latest`, but it was some time ago. It's influx version `2.7.6`, CLI vesion `2.7.3`.
- CPU: AMD Ryzen 7 5700U
- Memory: 5GB was allocated to the image, now testing on 16GB, although container never ran out of memory while querying this data.

## Operating System:

Laptop:

Ubuntu 22.04.4 LTS x86_64

Docker image:

Linux 36a415262a30 6.4.16-linuxkit #1 SMP PREEMPT_DYNAMIC Fri Nov 10 14:51:57 UTC 2023 x86_64 GNU/Linux

## Code Editing Tool:

PyCharm and influx in browser control panel

## Build Environment:
Docker. influx:latest. Influx version `2.7.6`, CLI vesion `2.7.3`.

The issue names no repository files, tests, or entry points. Start by reproducing the Flux geo query with the NOAA dataset and the documented InfluxDB 2.7.6 Docker setup; done means establishing whether the reported latency is reproducible and identifying a documented or testable performance improvement.

Written by the indexing model from the issue text.