Esri EGMP2201 Exam Questions

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.

Reference from Esri Documentation and Learning Resources:

Map Caching in ArcGIS Enterprise

Best Practices for Map Services

Conclusion:

The GIS administrator should recommend enabling cached data for the zoomed extents to significantly improve map performance.

For a large government organization requiring an equivalent data presence in a standby data center, database replication is the ideal solution.

1. What is Database Replication?

Database replication involves duplicating data from a primary database to a secondary database in near real-time or on a scheduled basis.

This ensures that both databases are synchronized and capable of serving data if one fails.

2. Why Database Replication Fits the Requirement

Standby Data Center: Database replication provides a fully equivalent copy of the data in the secondary data center.

High Availability and Disaster Recovery: If the primary database is unavailable, the standby database can immediately take over, ensuring business continuity.

3. Why Not Other Options?

Geodatabase Replication:

While it is designed for replicating geodatabase content, it is typically used for GIS-specific workflows, such as syncing field edits. It does not ensure equivalence for non-spatial components of the database.

It is not ideal for large-scale, organization-wide replication needs.

Disconnected Synchronization:

This is used in offline editing workflows where devices sync their edits with a central database at a later time. It is not suitable for maintaining an equivalent standby database.

4. Types of Database Replication

Asynchronous Replication: Updates are replicated at scheduled intervals, offering flexibility but with slight delays.

Synchronous Replication: Updates occur in real-time, ensuring both databases are always identical.

Steps to Implement Database Replication:

Configure the primary and standby databases in the organization's DBMS (e.g., SQL Server, PostgreSQL, Oracle).

Use the DBMS's built-in replication tools (e.g., SQL Server's Always On, PostgreSQL's Streaming Replication).

Set up monitoring to ensure the replication process is functioning correctly.

Reference from Esri Documentation and Learning Resources:

Database Replication in DBMS

Disaster Recovery with Database Replication

Conclusion:

Database replication is the recommended technology to establish an equivalent data presence in a standby data center, ensuring high availability and disaster recovery.

Understanding the Scenario:

A two-way replica exists between a parent geodatabase and a child geodatabase to share edits.

A schema change (adding the legal_area field) occurs in the parent geodatabase but is not applied to the child geodatabase.

The parent synchronizes the replica, attempting to push changes that include edits to the new field.

Replica Synchronization Behavior:

Schema Changes and Replication: Replication does not automatically synchronize schema changes such as adding new fields. Schema updates need to be manually applied to both parent and child geodatabases before synchronization.

Conflict during Synchronization: If schema changes (like adding a field) are made in the parent geodatabase but not replicated in the child geodatabase, synchronization attempts to apply edits referencing the missing field. This results in an error because the child geodatabase does not recognize the new field.

Reference:

Esri Documentation: Schema Changes and Replication.

Error Handling in Synchronization: Guidance on managing synchronization issues due to schema mismatches.

Why the Correct Answer is A: During synchronization, an error occurs because the legal_area field does not exist in the child geodatabase. Synchronization cannot succeed unless both replicas have compatible schemas.

For a large government organization requiring an equivalent data presence in a standby data center, database replication is the ideal solution.

1. What is Database Replication?

Database replication involves duplicating data from a primary database to a secondary database in near real-time or on a scheduled basis.

This ensures that both databases are synchronized and capable of serving data if one fails.

2. Why Database Replication Fits the Requirement

Standby Data Center: Database replication provides a fully equivalent copy of the data in the secondary data center.

High Availability and Disaster Recovery: If the primary database is unavailable, the standby database can immediately take over, ensuring business continuity.

3. Why Not Other Options?

Geodatabase Replication:

While it is designed for replicating geodatabase content, it is typically used for GIS-specific workflows, such as syncing field edits. It does not ensure equivalence for non-spatial components of the database.

It is not ideal for large-scale, organization-wide replication needs.

Disconnected Synchronization:

This is used in offline editing workflows where devices sync their edits with a central database at a later time. It is not suitable for maintaining an equivalent standby database.

4. Types of Database Replication

Asynchronous Replication: Updates are replicated at scheduled intervals, offering flexibility but with slight delays.

Synchronous Replication: Updates occur in real-time, ensuring both databases are always identical.

Steps to Implement Database Replication:

Configure the primary and standby databases in the organization's DBMS (e.g., SQL Server, PostgreSQL, Oracle).

Use the DBMS's built-in replication tools (e.g., SQL Server's Always On, PostgreSQL's Streaming Replication).

Set up monitoring to ensure the replication process is functioning correctly.

Reference from Esri Documentation and Learning Resources:

Database Replication in DBMS

Disaster Recovery with Database Replication

Conclusion:

Database replication is the recommended technology to establish an equivalent data presence in a standby data center, ensuring high availability and disaster recovery.

The issue arises because the standard database view is based on the base table of the points feature class, which does not include edits made in child versions. To resolve this, the database view must reference a versioned view to reflect changes in the Default version.

1. What Is a Versioned View?

A versioned view is created when a feature class is registered as versioned.

It allows querying and editing versioned data, including edits made in the Default version and child versions.

A standard database view does not account for the Adds and Deletes delta tables used in versioning, which is why edits are not visible.

2. Why Alter the View to Use a Versioned View?

By modifying the standard database view to reference the versioned view, the published web layer will reflect changes made in the Default version, including ongoing edits.

This ensures that updates to the points feature class are visible in the web layer without requiring manual intervention.

3. Why Not Other Options?

Have All Editors Reconcile and Post Points Edits to Default:

While this ensures edits are moved to the Default version, it requires continuous manual reconciliation and posting, which is impractical for a frequently edited dataset.

Rebuild Indexes and Calculate Database Statistics on Points:

These actions improve query performance but do not address the core issue of the standard view not reflecting versioned edits.

Steps to Alter the View:

Identify the versioned view associated with the points feature class. It typically has a name like points_EVW.

Modify the SQL for the existing view to reference the versioned view:

CREATE OR REPLACE VIEW points_web AS

SELECT <fields> FROM points_EVW;

Update the web layer to use the modified view as the data source.

Test the web layer to confirm that edits made to the Default version are now visible.

Reference from Esri Documentation and Learning Resources:

Publishing Data from Views

Conclusion:

To ensure edits made to the points feature class are visible in the web layer, the database view should be altered to reference the versioned view, which accounts for edits in the Default version.