How to batch rebuild spatial indexes of feature classes in an ArcSDE database

When changes to data affect the index, the information in the index can be spread out across the database. Reindexing reorganizes the storage of indexed data (and in the case of clustered indexes, table data) and defragments it. This improves disk performance by reducing the number of page reads required to obtain the requested data.

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Generally, when importing a layer to the SDE database, it will automatically establish a grid index by default, which has been optimized based on the spatial reference of the layer, the type of the drawing and other relevant information. 1. Introduction to SDE Spatial IndexArcSDE Spatial Query adopts the grid index mechanism, so the setting of the size of the index network can directly affect the response and system of the data.

Spatial indexes of vector data.

In relational databases, the indexing of attribute items can speed up the query of attribute data, similarly, arcsde reduces the shape-shape comparison operation by establishing a spatial index table (or s table) of the layer, and the number of records returned from the database is reduced by using spatial filters on the client side of arcsde, which can avoid retrieving the entire table, reduce the number of retrieved data records, thereby reducing the input and output operations of data, and speeding up the speed of spatial data query (etc., 2000）。

ARCSED uses the Trace-Watching Grid index. The grid index is a square grid that divides the spatial area into a square grid of appropriate size, recording the spatial entities (objects) contained in each grid, as well as the encapsulated boundary range of each entity, that is, the coordinates of the lower left and upper right corners that enclose the spatial entity. When a user performs a spatial query, the grid where the user query object is located is first calculated, and then the required spatial entity can be quickly retrieved through the grid number.

Therefore, determining the appropriate grid series and cell size is the key to establishing a spatial grid index. The size of the grid cells is not a definitive problem and requires multiple attempts to get there. The grid is too large, and there are multiple spatial entities within a grid, and the query retrieval accuracy is low.

If the grid is too small, the number of indexes will grow exponentially and be redundant, and the speed and efficiency of retrieval will be low. In order to improve the work efficiency of the database, each data layer in the basic database of land and resources remote sensing comprehensive survey adopts spatial index grid cells of different sizes and different progressions.

Spatial index of raster data.

The spatial indexing of raster data can be achieved by establishing a multi-level pyramid structure. The pyramid structure is a reflection of the decreasing resolution of a raster dataset and is used to provide display-order performance. The purpose of building a pyramid is to optimize the performance and efficiency of the display.

The resolution at the bottom of the pyramid is always the highest, decreasing upwards. Pyramids improve raster display order performance by only taking data at the appropriate resolution that meets the display requirements, when a pyramid is built, more rasters will be created until the fixed point or layer limit is reached, and when the application zooms out or the grid squares are less than the resolution threshold, ArcSDE will choose a higher level in the pyramid. Each raster dataset can be pyramided in different levels depending on its data resolution.

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