Esri EGMP2201 Exam With Confidence Using Practice Dumps

The slow performance at zoomed-out extents is likely caused by the rendering of complex polygon geometries in real time, which can be computationally intensive. Using cached data is the best approach to improve performance in this situation.

1. Reason for Slow Performance at Zoomed-Out Extents

Complex polygons require significant processing power to render at smaller scales due to the high number of vertices and complex geometry.

When users zoom out, the number of features being displayed increases, causing additional strain on the map service.

Attribute queries are not affected because they do not involve rendering the geometries.

2. Advantages of Using Cached Data

Cached tiles are pre-rendered images of the map at specific scales, stored on the server.

When cached data is used, the server simply retrieves and displays these images instead of dynamically rendering the features.

This drastically reduces server load and improves map performance at zoomed-out extents.

3. Why Not Other Options?

Run the Analyze Datasets Tool:

This tool checks for issues like invalid geometries, missing spatial indexes, or improper field types. While useful for general data health, it does not directly address rendering performance.

Compress the Enterprise Geodatabase:

Compression improves performance for versioned data by consolidating states and cleaning up the database. However, in this case, the feature class is not versioned, so compression would not resolve the rendering issues.

Steps to Implement Caching:

Open ArcGIS Server Manager and navigate to the map service configuration.

Enable tile caching and define the scales at which tiles should be created (include the problematic zoomed-out extents).

Generate the cache using the "Manage Map Server Cache Tiles" tool.

Test the map to ensure performance improvements.

References from Esri Documentation and Learning Resources:

Map Caching in ArcGIS Enterprise

Best Practices for Map Services

Conclusion:

The GIS administrator should recommend enablingcached data for the zoomed extentsto significantly improve map performance.

 Understanding the Scenario:

Records are being appended to a child version of a feature class registered as versioned.

Reconcile and post are taking longer than expected, suggesting complications during version synchronization.

 Key Considerations for Reconciliation Performance:

Conflicting Edits (Option A):Reconciliation time increases if there are many conflicts to resolve. However, the question does not mention concurrent edits in Default or other child versions, making conflicts less likely to be the main issue.

Updates in Default (Option B):If Default has been updated since the child version was created, the reconcile process must account for changes in Default. This can significantly increase processing time as it integrates the child version changes with the modifications in Default.

Compress Operation (Option C):The Compress operation removes redundant states in the geodatabase but does not directly affect reconciliation speed. The question does not indicate that the child version is excluded from compression or that compression is related to the delay.

 Steps to Improve Reconciliation Performance:

Minimize edits to Default during the child version's workflow.

Reconcile frequently to avoid large differences between Default and the child version.

Ensure that Compress operations are run regularly to optimize geodatabase state management.

 References:

Esri Documentation: Reconcile and Post.

Versioning Best Practices: Guidance on managing Default and child versions to minimize reconcile conflicts.

 Why the Correct Answer is B:The delay occurs because Default was updated after the child version was created. The reconciliation process must merge changes from Default with those in the child version, increasing processing time. Conflicts (A) are not mentioned, and compress operations (C) do not directly cause reconciliation delays.

To restrict access to specific fields in a feature class, the GIS data administrator should use adatabase view.

1. What is a Database View?

Adatabase viewis a virtual table created by a SQL query. It displays data from one or more tables or feature classes, but only the specified fields and rows are accessible.

Views allow the administrator to control the fields and records visible to users without altering the underlying data.

2. Why Use a Database View?

Provides fine-grained control over data access by limiting which fields (or rows) are visible to specific users.

Helps enforce data security policies in multi-user environments.

Can be shared as a read-only layer or with restricted update permissions, depending on the use case.

3. Why Not Other Options?

Layer File:

A layer file (*.lyr) only defines how data is symbolized and displayed. It does not restrict field access at the database level. Unauthorized users can still access hidden fields through direct database connections.

Query Layer:

A query layer allows for custom SQL queries when displaying data in ArcGIS but is not a security measure. Users can modify or bypass the query to access all fields.

Steps to Create a Database View:

Use SQL to define the view, specifying only the required fields:

CREATE VIEW restricted_view AS

SELECT field1, field2

FROM feature_class

WHERE ;

Grant permissions to the view for authorized users while restricting access to the base table.

Publish the view in ArcGIS as a read-only layer if needed.

References from Esri Documentation and Learning Resources:

Creating and Using Database Views

Data Security in Enterprise Geodatabases

Conclusion:

Adatabase viewis the most effective method to restrict access to specific fields in a feature class, ensuring data security while providing flexibility in data sharing.