Manage Feature Bin Cache (Data Management)

Summary

Manages the feature binning cache for data with feature binning enabled.

Feature binning aggregates large amounts of point features into dynamic polygon bins that vary through scaled levels of detail. Learn how to enable feature binning and work with binned feature layers.

Usage

• Use this tool when feature binning has been enabled on a feature class and a static cache has been generated. If the underlying data has changed, run this tool to update the cache to reflect the most recent state of the data. If you run this tool on a feature class without a static cache, a static cache is generated. Use this tool to add or delete summary statistics that are stored in the cache or to modify the cache level of detail.

• Feature binning is only supported for point and multipoint feature classes stored in an enterprise geodatabase or database on the following platforms:

  • BigQuery
  • IBM Db2
  • Microsoft SQL Server
  • Oracle
  • PostgreSQL
  • SAP HANA
  • Snowflake
  However, because aggregated results are not cached for bins in SAP HANA, this tool is not needed or supported for SAP HANA data.

• Use the Level of Detail parameter to specify the maximum level of detail for the tiling scheme to include in the cache. Tiling schemes are a continuum of scale ranges. Depending on your map, you may want to forego caching of some of the extremely large or small scales in your tiling scheme. Choose a level of detail that most closely matches the intended use of the map in which the data will be shown.

Parameters

Dialog

Label	Explanation	Data Type
Input Features	The binning-enabled feature class that will have its static cache updated.	Feature Layer
Bin Type (Optional)	Specifies the type of binning that will be enabled. If you are using SAP HANA data, only Square, Flat hexagon, and Pointy hexagon options are supported. This parameter is not supported for BigQuery or Snowflake data. Flat hexagon—A binning scheme that is also known as flat geohex or flat hexbinning. The tiles are a tessellation of hexagons in which the orientation of the hexagons has a flat edge of the hexagon on top. This is the default for Microsoft SQL Server, Oracle, and PostgreSQL data. Pointy hexagon—A binning scheme that is also known as pointy geohex or pointy hexbinning. The tiles are a tessellation of hexagons in which the orientation of the hexagons has a point of the hexagon on top. Square—A binning scheme in which the tiles are a tessellation of squares, also known as geosquare or squarebinning. This is the default for Db2 and SAP HANA data. Geohash—A binning scheme in which the tiles are a tessellation of rectangles. Because geohash bins always use the WGS84 geographic coordinate system (GCS WGS84, EPSG WKID 4326), you cannot specify a bin coordinate system for geohash bins.	String
Level of Detail (Optional)	Specifies the maximum level of detail that will be used for the cache. This parameter is not supported for BigQuery or Snowflake data. Tiling schemes are a continuum of scale ranges. Depending on your map, you may want to forego caching of some of the extremely large or small scales in your tiling scheme. This tool examines the scale dependencies in the map and attempts to provide a maximum range of scale for caching. Choose a level of detail that most closely matches the intended use of the map in which the data will be shown. World—A world scale will be used as the maximum level of detail. Continents—Multiple continents scale will be used as the maximum level of detail. Continent—A single continent scale will be used as the maximum level of detail. Countries—Multiple countries scale will be used as the maximum level of detail. Country—A single country scale will be used as the maximum level of detail. States—Multiple states scale will be used as the maximum level of detail. State—A single state scale will be used as the maximum level of detail. Counties—Multiple counties scale will be used as the maximum level of detail. County—A single county scale will be used as the maximum level of detail. Cities—Multiple cities scale will be used as the maximum level of detail. City—A single city scale will be used as the maximum level of detail.	String
Add Statistic to Cache (Optional)	Specifies the statistics that will be summarized and stored in the bin cache. Statistics are used to symbolize bins and provide aggregate information for all the points in a bin. One summary statistic, shape_count (which is the total feature count), is always available. Field—The field on which to calculate the summary statistics. Supported field types are short, long, float, and double. Statistic Type—The type of statistic to calculate for the specified field. Statistics are calculated for all features in the bin. Available statistics types are as follows: Mean (AVG)—Calculates the average for the specified field. Minimum (MIN)—Finds the smallest value for all records of the specified field. Maximum (MAX)—Finds the largest value for all records of the specified field. Standard deviation (STDDEV)—Calculates the standard deviation value for the field. Sum (SUM)—Adds the total value for the specified field.	Value Table
Delete Statistic from Cache (Optional)	The summary statistic that will be deleted from the cache. You cannot delete the default COUNT summary statistic.	String

Derived Output

Label	Explanation	Data Type
Updated Features	The input features with the updated feature bin cache.	Feature Layer

Python

arcpy.management.ManageFeatureBinCache(in_features, {bin_type}, {max_lod}, {add_cache_statistics}, {delete_cache_statistics})

Name	Explanation	Data Type
in_features	The binning-enabled feature class that will have its static cache updated.	Feature Layer
bin_type (Optional)	Specifies the type of binning that will be enabled. If you are using SAP HANA data, only SQUARE, FLAT_HEXAGON, and POINTY_HEXAGON options are supported. This parameter is not supported for BigQuery or Snowflake data. FLAT_HEXAGON—A binning scheme that is also known as flat geohex or flat hexbinning. The tiles are a tessellation of hexagons in which the orientation of the hexagons has a flat edge of the hexagon on top. This is the default for Microsoft SQL Server, Oracle, and PostgreSQL data. POINTY_HEXAGON—A binning scheme that is also known as pointy geohex or pointy hexbinning. The tiles are a tessellation of hexagons in which the orientation of the hexagons has a point of the hexagon on top. SQUARE—A binning scheme in which the tiles are a tessellation of squares, also known as geosquare or squarebinning. This is the default for Db2 and SAP HANA data. GEOHASH—A binning scheme in which the tiles are a tessellation of rectangles. Because geohash bins always use the WGS84 geographic coordinate system (GCS WGS84, EPSG WKID 4326), you cannot specify a bin coordinate system for geohash bins.	String
max_lod (Optional)	Specifies the maximum level of detail that will be used for the cache. This parameter is not supported for BigQuery or Snowflake data. Tiling schemes are a continuum of scale ranges. Depending on your map, you may want to forego caching of some of the extremely large or small scales in your tiling scheme. This tool examines the scale dependencies in the map and attempts to provide a maximum range of scale for caching. Choose a level of detail that most closely matches the intended use of the map in which the data will be shown. WORLD—A world scale will be used as the maximum level of detail. CONTINENTS—Multiple continents scale will be used as the maximum level of detail. CONTINENT—A single continent scale will be used as the maximum level of detail. COUNTRIES—Multiple countries scale will be used as the maximum level of detail. COUNTRY—A single country scale will be used as the maximum level of detail. STATES—Multiple states scale will be used as the maximum level of detail. STATE—A single state scale will be used as the maximum level of detail. COUNTIES—Multiple counties scale will be used as the maximum level of detail. COUNTY—A single county scale will be used as the maximum level of detail. CITIES—Multiple cities scale will be used as the maximum level of detail. CITY—A single city scale will be used as the maximum level of detail.	String
add_cache_statistics [[Field, Statistic Type],...] (Optional)	Specifies the statistics that will be summarized and stored in the bin cache. Statistics are used to symbolize bins and provide aggregate information for all the points in a bin. One summary statistic, shape_count (which is the total feature count), is always available. Field—The field on which to calculate the summary statistics. Supported field types are short, long, float, and double. Statistic Type—The type of statistic to calculate for the specified field. Statistics are calculated for all features in the bin. Available statistics types are as follows: Mean (AVG)—Calculates the average for the specified field. Minimum (MIN)—Finds the smallest value for all records of the specified field. Maximum (MAX)—Finds the largest value for all records of the specified field. Standard deviation (STDDEV)—Calculates the standard deviation value for the field. Sum (SUM)—Adds the total value for the specified field.	Value Table
delete_cache_statistics [delete_cache_statistics,...] (Optional)	The summary statistic that will be deleted from the cache. You cannot delete the default COUNT summary statistic.	String

Derived Output

Name	Explanation	Data Type
out_features	The input features with the updated feature bin cache.	Feature Layer

Code sample

ManageFeatureBinCache example (Python window)

Add a new statistic to calculate the maximum depth and set the level of detail of the feature bin cache for a feature layer named Earthquakes.

import arcpy
arcpy.ManageFeatureBinCache_management("lod_gdb.elec.Earthquakes", "SQUARE", 
                                       "STATE", "depth_km MAX")

Environments

Current Workspace

Licensing information

• Basic: Yes
• Standard: Yes
• Advanced: Yes