Most Recent Esri EGMP2201 Exam Dumps

Scenario Overview:

The organization has a web service that must always be available.

The service reads data from a feature class in an enterprise geodatabase.

The GIS administrator needs to update the schema of the feature class.

Why Disable Schema Locking?

By default, ArcGIS services enforce schema locking to ensure data consistency while the service is active. This prevents any modifications to the feature class schema (e.g., adding fields, altering attributes) while the service is running.

Disabling schema locking allows schema updates to occur without disrupting the service's availability. (ArcGIS Documentation: Schema Locking)

Steps to Disable Schema Locking:

Access the ArcGIS Server Manager.

Locate the web service and open its service properties.

In the advanced settings, disable the schema locking option.

Perform the required schema updates (e.g., adding fields or modifying the feature class).

Re-enable schema locking if necessary for normal operation.

Alternative Options:

Option B: Run the Alter Field geoprocessing tool

This tool modifies fields but cannot execute schema changes while schema locks are active.

Option C: Delete the spatial index

Deleting the spatial index is unrelated to schema changes and could degrade query performance.

Thus, the correct workflow is to disable schema locking on the service to allow schema changes without disrupting the web service.

To minimize the number of rows created in the database while performing versioning workflows (loading, quality checking, reconciling, and posting), Traditional versioning without the archiving option is the best choice.

1. Traditional Versioning Without Archiving

This method stores edits in delta tables (Adds and Deletes) rather than directly in the base table.

Without the archiving option, the system does not create additional rows to track historical changes, which helps reduce the number of rows.

2. Why It's Ideal for This Workflow

Load Data: Data is directly inserted into the delta tables, keeping base tables untouched.

Quality Verification: Edits can be reviewed and adjusted without additional overhead.

Reconcile and Post: Only the changes made during the session are pushed to the default version, and unnecessary rows are avoided.

3. Why Not Other Options?

Traditional Versioning with Archiving Option:

Archiving tracks historical changes, creating additional rows for each edit in the archive tables. This increases storage and processing overhead.

Branch Versioning:

Branch versioning stores all changes in a single table and is designed for web services workflows. It may not minimize row creation compared to traditional versioning.

Steps for the Workflow:

Enable Traditional Versioning for the target dataset without enabling archiving.

Load the large dataset into a new version created for this purpose.

Verify the data quality by querying and editing the version.

Reconcile the version with the default version, resolve conflicts, and post changes to default.

Reference from Esri Documentation and Learning Resources:

Understanding Traditional Versioning

Archiving in Enterprise Geodatabases

Branch Versioning vs. Traditional Versioning

Conclusion:

Using Traditional versioning without the archiving option ensures the creation of the fewest number of rows while maintaining data integrity and supporting the described workflow.

Understanding the Scenario:

The feature class is versioned and participates in a geodatabase topology.

The goal is to reload data while maintaining versioning and topology integrity.

Key Considerations for Reloading Data:

Truncate Table: The Truncate Table tool efficiently deletes all rows in the feature class without logging individual row deletions in the geodatabase. It is the preferred method for clearing data while minimizing impact on performance.

Append Tool: After truncating the table, the Append tool can load new data into the feature class, ensuring that the topology and versioning structure remain intact.

Avoiding Delete Rows: Deleting rows manually logs each deletion in delta tables, leading to a potential performance bottleneck and unnecessary transaction logging, especially for versioned datasets.

Geodatabase Topology Consideration: Topology rules will need to be validated after reloading the data to ensure spatial integrity.

Steps to Reload Data:

Use the Truncate Table tool to remove existing records.

Use the Append tool to load the new data into the feature class.

Validate the topology in the geodatabase to check for any errors after the reload.

Reference:

Esri Documentation: Truncate Table.

Loading Data into Versioned Feature Classes: Best practices for versioned and topology-aware datasets.

Why the Correct Answer is A: Running the Truncate Table tool ensures efficient data clearing, and using the Append tool maintains the geodatabase's versioning and topology structure. Options B and C involve unnecessary row-level deletions, which are inefficient and could disrupt the versioned workflow.

When experiencing slow performance on a query of an indexed attribute in a large feature class within an enterprise geodatabase, and a SQL trace reveals that the attribute index is not being utilized despite the attribute values having a high degree of uniqueness and the delta tables containing few rows, the appropriate action is to rebuild the indexes.

Understanding Indexes in Enterprise Geodatabases:

Indexes are critical for enhancing query performance in databases. They allow the database management system (DBMS) to locate and retrieve data efficiently. Over time, as data is inserted, updated, or deleted, indexes can become fragmented or outdated, leading to suboptimal query performance.

ARCGIS PRO

Rebuilding Indexes:

The Rebuild Indexes tool in ArcGIS Pro is designed to rebuild existing attribute or spatial indexes in enterprise geodatabases. This process reorganizes the index structure, ensuring that the DBMS can effectively utilize the indexes during query execution.

ARCGIS PRO

Steps to Rebuild Indexes:

Access the Rebuild Indexes Tool:

In ArcGIS Pro, navigate to the Analysis tab and click on Tools.

In the Geoprocessing pane, search for and select the Rebuild Indexes tool.

Configure the Tool Parameters:

Input Database Connection: Specify the connection to your enterprise geodatabase.

Include System Tables: Decide whether to include system tables in the rebuild process. Including system tables can help maintain the overall health of the geodatabase but may increase processing time.

Execute the Tool:

Click Run to initiate the index rebuilding process. Monitor the progress and ensure the process completes without errors.

Alternative Options:

Compress Geodatabase: The Compress operation reduces the size of the geodatabase by removing redundant states and versions. While it can improve performance, it doesn't directly address index fragmentation.

Analyze Datasets: The Analyze Datasets tool updates database statistics, which helps the DBMS optimize query execution plans. However, if indexes are fragmented, analyzing datasets alone may not resolve performance issues.

Given the symptoms described---specifically, the attribute index not being used in queries---the most effective solution is to rebuild the indexes to ensure they are properly structured and utilized by the DBMS during query execution.

Scenario Overview:

Editors are spending multiple hours resolving conflicts during reconciliation.

Key points:

Conflicts are detected by attribute (not by object).

Traditional versioning is used.

Weekly compression and weekly reconcile/post workflows are in place.

Why Reconcile and Post Daily?

Conflicts occur when multiple editors make overlapping edits. The longer versions remain unreconciled, the more conflicts accumulate, leading to time-consuming resolution.

Daily reconciliation and posting minimizes the number of changes between the parent and child versions, reducing the likelihood and volume of conflicts.

(ArcGIS Documentation: Reconcile and Post)

Key Benefits of Daily Reconciliation:

Fewer Changes to Compare: With fewer edits accumulated in each version, conflict detection is faster.

Less Complex Conflicts: Simplifies resolution since changes are smaller and more recent.

Improved Editor Productivity: Editors spend less time resolving conflicts, freeing up time for other tasks.

Alternative Options:

Option A: Detect conflicts by object

While this may reduce conflict granularity, it can lead to overwriting valid edits at the object level, which may not be acceptable in collaborative workflows.

Option B: Compress the geodatabase daily

Compression reduces the state tree and improves performance but does not directly reduce the number of conflicts during reconciliation.

Therefore, implementing daily reconciliation and posting is the most effective way to reduce conflicts and improve editing efficiency.