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D. The join between the tables order_detail and product needs to be fine-tuned due to Indices. This is correct because the result of the explain statement showsthat the join between these two tables has a high cost of 0.99, which indicates that it is inefficient and needs to be fine-tuned. One possible reason for the high cost is that there are no indices on the columns that are used for joining these two tables, which leads to a full table scan. Therefore, creating indices on these columns could improve the performance of this join.

E. The worst join is the one between the table order_detail and customer. This is correct because the result of the explain statement shows that the join between these two tables has a very high cost of 1.00, which indicates that it is the worst join in terms of efficiency and needs to be fine-tuned. One possible reason for the high cost is that there are no indices on the columns that are used for joining these two tables, which leads to a full table scan. Therefore, creating indices on these columns could improve the performance of this join.

The other options are incorrect for the following reasons:

A. The request is good enough to support a high volume of data, but could demonstrate some limitations if the developer queries information related to the product. This is incorrect because the request is not good enough to support a high volume of data, as it has two joins with very high costs that need to be fine-tuned. Moreover, querying information related to the product would not necessarily cause any limitations, as long as the join between order_detail and product is optimized.

B. The worst join is the one between the table order_detail and order. This is incorrect because the result of the explain statement shows that the join between these two tables has a low cost of 0.01, which indicates that it is efficient and does not need to be fine-tuned.

C. The join between the tables order_detail, order and customer needs to be fine-tuned due to indices. This is incorrect because there is no such join between three tables in the result of the explain statement. There are only two joins: one between order_detail and order, and another between order_detail and customer. Each of these joins needs to be fine-tuned separately due to indices.

Deploying an object that is dependent on another object from a different application can cause errors and inconsistencies in the production environment. The best practice is to halt the production deployment and contact the other team for guidance on how to promote the object to PROD. The other team may have a different deployment schedule, or they may have some dependencies or customizations that need to be considered. By communicating with the other team, you can ensure that the object is deployed in a safe and coordinated manner, and avoid any potential conflicts or issues. Verified References: [Appian Deployment Guide], [Appian Best Practices]

Functional acceptance criteria are the conditions that a user story must satisfy to be accepted by the user or stakeholder. They should be specific, measurable, achievable, relevant, and testable. In this case, two functional acceptance criteria that would be considered ‘good’ are:

The user will receive an email notification when their order is completed. This is a specific, measurable, achievable, relevant, and testable criterion that describes a feature that the user needs to be informed of their order status.

The user cannot submit the form without filling out all required fields. This is a specific, measurable, achievable, relevant, and testable criterion that describes afeature that the user needs to provide valid and complete information for their order.

The other options are not as good. Option A, the user will click Save, and the order information will be saved in the ORDER table and have audit history, is not a functional acceptance criterion, but rather a technical implementation detail that is not relevant or visible to the user. Option C, the system must handle up to 500 unique orders per day, is not a functional acceptance criterion, but rather a non-functional requirement that describes a performance or quality attribute of the system.

When creating a script to add a new field to a table, you should consider two actions:

Create a rollback script that removes the field. A rollback script is a script that can undo the changes made by the original script, in case something goes wrongor the changes need to be reverted. A rollback script is a good practice to have, as it can help to restore the previous state of the database and avoid any errors or inconsistencies. In this case, the rollback script should remove the new field from the table, and any other changes that were made by the original script.

Create a script that adds the field and then populate it. A script that adds the field and then populate it is a script that can create the new field in the table, and then fill it with data from another table or source. This way, you can ensure that the new field has valid and consistent data, and that it can be used by the report in the upcoming release. In this case, the script should add the new field to the customer table, and then populate it with data from another table that contains the data used in the calculation.

Navigate to the Admin console > Authentication > LDAP. This is the first step, as it allows you to access the settings and options for LDAP authentication in Appian.

Work with the customer LDAP point of contact to obtain the LDAP authentication xsd. Import the xsd file in the Admin console. This is the second step, as it allows you to define the schema and structure of the LDAP data that will be used for authentication in Appian. You will need to work with the customer LDAP point of contact to obtain the xsd file that matches their LDAP server configuration and data model. You will then need to import the xsd file in the Admin console using the Import Schema button.

Enable LDAP and enter the LDAP parameters, such as the URL of the LDAP server and plaintext credentials. This is the third step, as it allows you to enable and configure the LDAP authentication in Appian. You will need to check the Enable LDAP checkbox and enter the required parameters, such as the URL of the LDAP server, the plaintext credentials for connecting to the LDAP server, and the base DN for searching for users in the LDAP server.

Test the LDAP integration and see if it succeeds. This is the fourth and final step, as it allows you to verify and validate that the LDAP authentication is working properly in Appian. You will need to use the Test Connection button to test if Appian can connect to the LDAP server successfully. You will also need to use the Test User Lookup button to test if Appian can find and authenticate a user from the LDAP server using their username and password.

To design a process that is anticipated to be executed multiple times a day, that retrieves data from an external system and then calls various utility processes as needed, you should use Process Messaging to start the utility process and minimize the load on the execution engines. Process Messaging is a feature that allows you to send and receive messages between processes in Appian. By using Process Messaging, you can start the utility process asynchronously, which means that the main process does not have to wait for the utility process to finish before continuing. This way, you can improve the performance and scalability of your process design, and reduce the load on the execution engines.

The other options are not as effective. Option A, using the Start Process Smart Service to start the utility processes, would also start the utility process asynchronously, but it would require more configuration and maintenance than Process Messaging. Option B, starting the utility processes via a subprocess synchronously, would start the utility process as a part of the main process flow, which means that the main process would have to wait for the utility process to finish before continuing. This would reduce the performance and scalability of your process design, and increase the load on the execution engines. Option D, starting the utility processes via a subprocess asynchronously, would also start the utility process as a part of the main process flow,but it would not wait for the utility process to finish before continuing. However, this option would still create more overhead than Process Messaging, as it would create more instances of processes in Appian.

Adding more engine replicas will increase the number of threads available to execute unattended process activities, such as timer events and sending notification emails. This will reduce the Java Work Queue Size and improve the performance of the application. Verified References: Appian Engine Performance Logs, Appian Engine Configuration

To create an integration from your Appian cloud instance to an application hosted within a customer’s self-managed environment, you need to ensure that there is a secure and reliable connection between the two systems. One way to do this is to set up a VPN tunnel, which is a virtual private network that encrypts and transports data over the internet. A VPN tunnel allows you to access the customer’s internal network and API endpoint from your Appian cloud instance, without exposing them to the public internet. This way, you can ensure the security and privacy of the data that is exchanged between the two systems. Verified References: [Appian Cloud VPN], [Appian Integration Guide]

To meet the application requirement of allowing users to view summary and detailed information about report data, you should implement a drilldown report pattern to show detailed information about report data. A drilldown report pattern is a user interface component that displays data in a hierarchical structure, and allows users to expand or collapse different levels of data. For example, if the user is viewing a sales report by region, the drilldown report pattern could show something like “North America > USA > California > Los Angeles”. The user can click on any level of data to see more or less details. This way, the user can see both summary and detailed information about report data, and explore different aspects of the data.

The other options are not as effective. Option A, using Tiles as Cards pattern on the home page to prominently display application choices, would provide a way for users to access different parts of the application from the home page, but it would not show summary or detailed information about report data. Option B, implementing an Activity History pattern to track an organization’s activity measures, would provide a way for users to see the recent actions performed by themselves or others in the application, but it would not show summary or detailed information about report data. Option D, including a breadcrumbs pattern on applicable interfaces to show the organizational hierarchy, would provide a way for users to see where they are in the application, and easily go back to any previous level by clicking on the corresponding link, but it would not show summary or detailed information about report data.