Minimizing Database Queries in PHP App Engine Standard with Cloud SQL

A.

To minimize the number of queries to the Cloud SQL backend for a PHP App Engine Standard service, we can use Memcache, a distributed, in-memory caching system that can store frequently accessed data. This approach can help reduce the latency and cost associated with querying the database repeatedly.

Of the four options provided, Option A is the correct answer. Here's why:

Option A: Set the memcache service level to dedicated. Create a key from the hash of the query, and return database values from memcache before issuing a query to Cloud SQL.

Explanation:

• Set the memcache service level to dedicated: Memcache comes in two service levels - shared and dedicated. In a shared service level, multiple applications share the same pool of Memcache instances, whereas in a dedicated service level, the instances are exclusively allocated to the application. Choosing a dedicated service level ensures that the cache is available only to our application and reduces the chances of cache contention and data corruption.

• Create a key from the hash of the query: To use Memcache, we need to create a unique key for each query we want to cache. We can generate this key by hashing the query string, which provides a deterministic and unique identifier for the query.

• Return database values from Memcache before issuing a query to Cloud SQL: Once we have generated a key for the query, we can check if the key exists in Memcache. If the key exists, we can retrieve the result from Memcache and return it to the user without querying the database. If the key does not exist, we can issue a query to Cloud SQL, retrieve the result, cache it in Memcache using the key, and then return it to the user.

Option B: Set the memcache service level to dedicated. Create a cron task that runs every minute to populate the cache with keys containing query results.

Explanation:

• Set the memcache service level to dedicated: Same as Option A.

• Create a cron task that runs every minute to populate the cache with keys containing query results: This option suggests using a cron task, a time-based job scheduler, to populate the cache with query results. While this approach can help prime the cache with frequently accessed data, it does not avoid the need to query the database every time a new query is encountered.

Option C: Set the memcache service level to shared. Create a cron task that runs every minute to save all expected queries to a key called cached_queries.

Explanation:

• Set the memcache service level to shared: In this option, we are using a shared Memcache service level, which means that multiple applications can access the same cache pool. This can lead to cache contention and data corruption.

• Create a cron task that runs every minute to save all expected queries to a key called cached_queries: This option suggests using a cron task to save all expected queries to a single key called cached_queries. However, this approach does not account for the possibility of multiple queries with different parameters, which would require different cache keys. Also, using a shared cache key for all queries can lead to cache thrashing and reduced cache hit rates.

Option D: Set the memcache service level to shared. Create a key called cached_queries, and return database values from the key before using a query to Cloud SQL.

Explanation:

• Set the memcache service level to shared: Same as Option C.

• Create a key called cached_queries, and return database values from the key before using a query to Cloud SQL: This option suggests using a single key called cached_queries to cache all queries. This approach suffers from the same drawbacks as Option C, namely cache thrashing and reduced cache hit rates. Additionally, using a single cache key for all queries can lead to cache pollution, where outdated query results remain in the cache indefinitely