Salesforce Data Architecture and Management Designer Exam Questions and Answers Already Passed
What is Multitenancy? - Answers Multitenancy is a means of providing a single application to multiple
organizations from a single hardware/software stack.
What does Salesforce do when providing its CRM to a new customer? - Answers Instead of providing a
complete set of hardware/software resources to an organization, Salesforce inserts a layer of software
between the single instance and other customer deployments. This layer is invisible to the organizations,
which only see their own data and schemas while Salesforce reorganizes the data behind the scenes to
perform efficient operations.
How does Salesforce ensure that tenant-specific customizations do not breach the security of other
tenants or affect their performance? - Answers Salesforce uses a runtime engine that generates
application components for each organization using the customer's metadata.
How does Salesforce store the application data for each organization? - Answers In a few large database
tables that are partitioned by tenant and serve as heap storage. The platform's runtime engine then
materializes virtual tables based on the customer's metadata.
What are two side-effects of the way that Salesforce stores customer application data? - Answers 1.)
Traditional performance-tuning techniques will show little to no results.
2.) You cannot optimize the underlying SQL of the application because it is generated by the system, and
not written by each tenant.
How long might it take before the text in a searchable object's created or updated record is searchable?
- Answers 15 minutes or more
In what order does Salesforce perform indexed searches? - Answers 1.) Searches the indexes for
appropriate records
2.) Narrows down the results by access permissions, search limits, and other filters, creating a result set
3.) Once a result set reaches a predetermined size, all other records are discarded
4.) Finally, the result set is used to query the records from the database to retrieve the fields that a user
sees
What are the main areas of the application that are impacted by differing (or suboptimal) architectures
in implementations with large data volumes? - Answers 1.) The loading or updating of large numbers of
records, either directly or with integrations.
2.) Extracting records using reports, list views, or queries.
What is the Force.com Query Optimizer? - Answers The Force.com Query Optimizer works behind the
scenes to determine the best path to the data being requested based on the filters in the query. It will
, determine the best index from which to drive the query, the best table from which to drive the query if
no good index is available, and more.
What is PK Chunking? - Answers PK Chunking (or Primary Key Chunking) is a strategy for querying large
data sets. PK Chunking is a feature of the Bulk API that splits a query into chunks of records with
sequential record Ids (i.e. the Primary Keys). Ids are always indexed, so this is an efficient method for
querying large data sets.
When would you use PK Chunking? - Answers When you need to query or extract 10s or 100s of millions
or records, for example, when you need to initially query an entire data set to setup a replicated
database, or if you need to query a set of data as part of an archival strategy where the record count
could be in the millions.
What is the default size for a PK Chunk? - Answers 100,000 records
What is the maximum size for a PK Chunk? - Answers 250,000 records
What is the most efficient chunk size (recommended) for an organization? - Answers It depends on a
number of factors, such as the data volume, and the filters of the query. Customers may need to
experiment with different chunk sizes to determine what is most optimal for their implementation.
100,000 records is the default size, with chunks able to reach 250,000 records per chunk, but the
increase in records per chunk means less efficiency in performance.
What is the format of the header to include in the Bulk API to enable PK Chunking? - Answers Sforce-
Enable-PKChunking
When using PK Chunking, how would you specify the chunk size in the header? - Answers Sforce-Enable-
PKChunking: chunkSize=100000;
What is a best practice for querying a supported object's share table using PK Chunking? - Answers
Determining the chunks is more efficient in this case if the boundaries are defined on the parent object
record Ids rather than the share table record Ids. So, for example, the following header could be used
for a Bulk API query against the OpportunityShare object table using PK Chunking:
Sforce-Enable-PKChunking: chunkSize=150000; parent=Opportunity
When loading data with parent references into Salesforce, what is more efficient? Using an External Id
or a Salesforce Id? - Answers Using an External Id has additional overhead in that it performs a kind of
"lookup" to find the record, whereas this additional overhead does not occur (or is bypassed) when
using the native Salesforce Id.
What is better? Performing Upserts, or performing Inserts followed by Updates? - Answers Upserts are
more costly than performing Inserts and Updates separately. Avoid Upserts when it comes to large data
volumes.
What is Multitenancy? - Answers Multitenancy is a means of providing a single application to multiple
organizations from a single hardware/software stack.
What does Salesforce do when providing its CRM to a new customer? - Answers Instead of providing a
complete set of hardware/software resources to an organization, Salesforce inserts a layer of software
between the single instance and other customer deployments. This layer is invisible to the organizations,
which only see their own data and schemas while Salesforce reorganizes the data behind the scenes to
perform efficient operations.
How does Salesforce ensure that tenant-specific customizations do not breach the security of other
tenants or affect their performance? - Answers Salesforce uses a runtime engine that generates
application components for each organization using the customer's metadata.
How does Salesforce store the application data for each organization? - Answers In a few large database
tables that are partitioned by tenant and serve as heap storage. The platform's runtime engine then
materializes virtual tables based on the customer's metadata.
What are two side-effects of the way that Salesforce stores customer application data? - Answers 1.)
Traditional performance-tuning techniques will show little to no results.
2.) You cannot optimize the underlying SQL of the application because it is generated by the system, and
not written by each tenant.
How long might it take before the text in a searchable object's created or updated record is searchable?
- Answers 15 minutes or more
In what order does Salesforce perform indexed searches? - Answers 1.) Searches the indexes for
appropriate records
2.) Narrows down the results by access permissions, search limits, and other filters, creating a result set
3.) Once a result set reaches a predetermined size, all other records are discarded
4.) Finally, the result set is used to query the records from the database to retrieve the fields that a user
sees
What are the main areas of the application that are impacted by differing (or suboptimal) architectures
in implementations with large data volumes? - Answers 1.) The loading or updating of large numbers of
records, either directly or with integrations.
2.) Extracting records using reports, list views, or queries.
What is the Force.com Query Optimizer? - Answers The Force.com Query Optimizer works behind the
scenes to determine the best path to the data being requested based on the filters in the query. It will
, determine the best index from which to drive the query, the best table from which to drive the query if
no good index is available, and more.
What is PK Chunking? - Answers PK Chunking (or Primary Key Chunking) is a strategy for querying large
data sets. PK Chunking is a feature of the Bulk API that splits a query into chunks of records with
sequential record Ids (i.e. the Primary Keys). Ids are always indexed, so this is an efficient method for
querying large data sets.
When would you use PK Chunking? - Answers When you need to query or extract 10s or 100s of millions
or records, for example, when you need to initially query an entire data set to setup a replicated
database, or if you need to query a set of data as part of an archival strategy where the record count
could be in the millions.
What is the default size for a PK Chunk? - Answers 100,000 records
What is the maximum size for a PK Chunk? - Answers 250,000 records
What is the most efficient chunk size (recommended) for an organization? - Answers It depends on a
number of factors, such as the data volume, and the filters of the query. Customers may need to
experiment with different chunk sizes to determine what is most optimal for their implementation.
100,000 records is the default size, with chunks able to reach 250,000 records per chunk, but the
increase in records per chunk means less efficiency in performance.
What is the format of the header to include in the Bulk API to enable PK Chunking? - Answers Sforce-
Enable-PKChunking
When using PK Chunking, how would you specify the chunk size in the header? - Answers Sforce-Enable-
PKChunking: chunkSize=100000;
What is a best practice for querying a supported object's share table using PK Chunking? - Answers
Determining the chunks is more efficient in this case if the boundaries are defined on the parent object
record Ids rather than the share table record Ids. So, for example, the following header could be used
for a Bulk API query against the OpportunityShare object table using PK Chunking:
Sforce-Enable-PKChunking: chunkSize=150000; parent=Opportunity
When loading data with parent references into Salesforce, what is more efficient? Using an External Id
or a Salesforce Id? - Answers Using an External Id has additional overhead in that it performs a kind of
"lookup" to find the record, whereas this additional overhead does not occur (or is bypassed) when
using the native Salesforce Id.
What is better? Performing Upserts, or performing Inserts followed by Updates? - Answers Upserts are
more costly than performing Inserts and Updates separately. Avoid Upserts when it comes to large data
volumes.
