Arcgis very slow

[joycemaia]

Hello!

Does anyone know how I can speed up the process Join Space ?. On my machine it has taken too long.

This is my setup

i5 3.0 GHz

8GB RAM

thanks

[joycemaia]

I followed the tip of all the comments.

1º

I created a geodabase with data

Added 4 shapes of polygons (countries, states, cities and districts of South America)

1 and the shape points (observation species)

2º

Join realized the Space as follows:

Analysis Tool-> overlay-> space join-> one to many

I think there is a difference in saving the job in the default output <inside geodatabase>,> takes longer to save in another way <another folder>

I realized that saving in another output <inside another folder> is faster. Only for some reason the ArcGIS is giving an error. This NEVER happened

He makes the table, but fails to display the map

As for time, it is almost the same thing! Tthe process is running forever.

Thus I modified the way cross data

Add the two shapes (polygons and points) on the desktop: right click (on top of the points layer) -> join and Relates

These methods are equivalent?

Thank you again!

[SepheFox]

Joyce, your geodatabase should be close to the root of your C drive, for example: C:\GIS_folder\test.gdb, and of course your shapefiles should all have the same projection.

Spatial Join joins the data by the location--one feature overlaps a feature in the other class, for instance.

Joins/relates joins data by a common field, such as a name or ID that is the same in each class.

So, they are not really the same--it depends what relates your two tables. If they are not related by location, then you should definitely use join/relate.

You are working with huge tables, as you said, so a spatial join will take a while.

[joycemaia]

See this is the file I'm working on:

https://www.dropbox.com/sh/b5bi24m8qjlyc5t/AAB-LY57CgAj0slEvljUzNk7a?dl=0

This file is in this directory: C: \ arc

[joycemaia]

I followed this tutorial:GIS Tutorial: How to perform a spatial join in ArcMap - YouTube

[DanPatterson_Retired]

It may just take a long time trying to do all the data at once.  Partitioning the inputs into smaller subsamples may speed things up since the sum of the parts may take less time than the whole

[joycemaia]

I'm doing this to know what kinds of points (bird species) have in each polygon (geopolitical regions). Then I will eliminate georeferenced data and remove the duplicates. I need such a table:

Country	Sp	Area	Perimeter
Canada	sp1	x	a
Canada	sp2	x	a
Canada	sp6	x	a
Canada	sp9	x	a
United States	sp9	y	b
United States	sp212	y	b
United States	sp63	y	b
United States	sp9	y	b
Argentina	sp1	z	c
Argentina	sp2	z	c
Argentina	sp6	z	c
Argentina	sp9	z	c
India	sp1	w	d
India	sp243	w	d
India	sp6	w	d
India	sp9	w	d
India	sp154	w	d
India	sp76	w	d
India	sp6	w	d

[SepheFox]

Hey Joyce, I tried running the spatial join, and it is taking a long time. I think you'll just have to wait for it to complete. You have 3 million points to analyze.

[DanPatterson_Retired]

if you have fewer countries than species you could partition by country or even continent. try to get your workflow for one condition, then you can automate.  for example some bird species summer in Canada and winter south of the equator...there is little point in having India or Australia in the spatial mix

[joycemaia]

You're right! Join and related is not good to do this. Look at :

The red points are related with in polygons information, and yellow points are original data.

For some reason it excludes some points. I expected to see a full overlay layers.

I will divide these files into smaller shapes!

Thank you all for trying to help me!

[SepheFox]

Yes, because your tables have no related field: that is a field which links the two of them. The only way they can be joined, is by their spatial location, as you are doing.