In this chapter, you have learned three new optimization techniques that can be performed to achieve optimal efficiency for file geodatabases. You worked with both spatial and attribute indexing, and you learned when to use each efficiently. You also learned that overusing indexing could cause a performance penalty if planned poorly. Then, you worked with compression, which helps drastically reduce the geodatabase size and save plenty of disk space. Finally, you learned how compacting can help speed up queries of a frequently edited geodatabase. The next chapter will discuss some scripting and programming techniques on how to manage and administer the geodatabase using the file geodatabase API.
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Hussein Nasser is an Esri award-winning senior GIS solution architect working in the GIS field since 2006. He is the author of three books in the ArcGIS technology: Administering ArcGIS for Server, Learning ArcGIS Geodatabases, and Building Web Applications with ArcGIS, all by Packt Publishing. In 2007, he won the first place at the annual ArcGIS Server Code Challenge, conducted at the Esri Developer Summit in Palm Springs, California. In 2014, he started the IGeometry YouTube channel, where he periodically publishes educational GIS videos.
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Hussein Nasser is an Esri award-winning senior GIS solution architect working in the GIS field since 2006. He is the author of three books in the ArcGIS technology: Administering ArcGIS for Server, Learning ArcGIS Geodatabases, and Building Web Applications with ArcGIS, all by Packt Publishing. In 2007, he won the first place at the annual ArcGIS Server Code Challenge, conducted at the Esri Developer Summit in Palm Springs, California. In 2014, he started the IGeometry YouTube channel, where he periodically publishes educational GIS videos.
Read more about Hussein Nasser