ACD300 Dumps With Exact Questions and Answers

The field would benefit greatly from the index in the following scenarios:

• A. The field contains a textual short Business code. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A textual short Business code is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.
• C. The field contains many datetimes, covering a large range. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A datetime field is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.
• D. The field contains big integers, above and below 0. This is a scenario where an index can improve the performance of queries that search for exact matches or ranges of values in the field. A big integer field is likely to have high cardinality, meaning that it has many distinct values and low duplication. This makes the index more selective and efficient, as it can quickly narrow down the results based on the search criteria.

The other options are incorrect for the following reasons:

• B. The field contains long unstructured text such as a hash. This is a scenario where an index might not improve the performance of queries that search for exact matches or ranges of values in the field. A long unstructured text field is likely to have low cardinality, meaning that it has few distinct values and high duplication. This makes the index less selective and efficient, as it cannot quickly narrow down the results based on the search criteria. Moreover, indexing a long unstructured text field could increase thestorage space and maintenance cost for the database, which could affect the overall performance.
• E. The field contains a structured JSON. This is a scenario where an index might not improve the performance of queries that search for exact matches or ranges of values in the field. A structured JSON field is not a native data type in MySQL, and it requires special functions or operators to access or manipulate its elements. Indexing a structured JSON field could increase the complexity and overhead for the database, which could affect the overall performance. Verified References: Appian Documentation, section “Query Optimization”.

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.

• 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.