Bulk API

Question 1

What is the max number of records that can be processed by Batch Apex

Answer 1

50 million

Question 2

How many GB of data can Bulk queries retrieved (and how are they divided up?)

Answer 2

Can retrieve up to 15GB of data, divided into 15 1GB files

Question 3

In which scenario would Batch Apex not work well?

Answer 3

Anything Synchronous like a VF page that needs to query more than 50,000 records

Question 4

What two operations does Bulk API support?

Answer 4

Query and queryAll

Question 5

What does the QueryAll operation do?

Answer 5

• Returns records that have been deleted because of a merge or delete
• Returns information about archived Task and Event records

Question 6

What time limit is there on executing bulk API queries, and what error is thrown?

Answer 6

2 minutes and it fails with QUERY_TIMEOUT

Question 7

For Bulk API, what happens when the results exceeds a 1GB file size (or takes longer than 10 minutes?)

Answer 7

The completed results are cached and another attempt is made.

Question 8

How many attempts are made for Bulk API when they timeout (or the file size is greater than 1GB), and what type of error is thrown

Answer 8

15. After that it fails with Retried more than 15 times.

Question 9

How long are Bulk API results stored?

Answer 9

7 days

Question 10

Which API would be good to use when loading a few thousand to millions of records

Answer 10

Bulk API

Question 11

On which principle is Bulk API based on?

Answer 11

REST

Question 12

What are the benefits for using Bulk API?

Answer 12

• Developed to simplify and optimize the process of loading or deleting large data sets
• Super-fast processing speeds
• Reduced client-side programmatic language
• Easy-to-monitor job status
• Automatic retry of failed records
• Support for parallel processing
• Minimal roundout trips to Force.com
• Minimal API calls
• Limited dropped connections
• Easy-to-tune batch size

Question 13

What is the default chunk size for Bulk API?

Answer 13

100,000 record chunks by default

Question 14

How can you configure the chunk size for Bulk API?

Answer 14

Use chunkSize header to configure smaller chunks or larger ones up to 250,000

Question 15

What is the maximum chunk size for Bulk API?

Answer 15

250,000

Question 16

What is the file size limit for Bulk API

Answer 16

10 MB

Question 17

What is the limit on the number of records that can be processed by the Bulk API?

Answer 17

10,000 records

Question 18

What is the maximum character data limit for all the data in a batch when using Bulk API?

Answer 18

10 Million characters data

Question 19

What is the character field Max limit for Bulk API?

Answer 19

32,000 characters

Question 20

What is the limit for fields per record for Bulk API?

Answer 20

5,000 fields

Question 21

What is the limit for all characters per record for Bulk API?

Answer 21

400,000 characters per record

Question 22

What is the max size of a file that can be loaded using Bulk API?

Answer 22

10MB

Question 23

For binary content, what is the max zip file size when using Bulk API?

Answer 23

10MB

Question 24

For binary content, what is the max total size of the unzipped content when using Bulk API?

Answer 24

The total size of the unzipped content can’t exceed 20MB

Question 25

What is the degree of parallelism

Answer 25

The amount of work completed (as a duration) divided by the actual amount of time it took to complete that work

Question 26

How does the Bulk API work? (3 main steps)

Answer 26

1. Data streamed in large batches directly to temporary storage over a simple HTTP connection (The client creates the job, send all data to server in batches, check status and at the end retrieve the result) 2. Data set is managed in a job that can be monitored and controlled (aborted) from Admin Setup (The jobs are then split into multiple data batches that will return multiple results) 3. Data set can be processed faster by allocating multiple servers to process in parallel (The Processing servers dequeue batch from job, insert or update records, save the results back to the job)

Question 27

Which of these is true about bulk queries? - Bulk API can access or query compound address and compound geolocation fields - Bulk queries always time out when querying more than 100,000 records - A bulk query can retrieve up to 15GB data divided into 1GB files - In order to keep results lean, bulk query does not support queryAll operations

Answer 27

A bulk query can retrieve up to 15GB data divided into | 1GB files

Question 28

Which of these is one of the advantages of using Bulk API when uploading large volumes of data? - Bulk API loads data in bite-size chunks, increasing the speed of jobs - Bulk API is optimized for real-time client applications - Bulk API only allows batches to be processed serially - Bulk API moves the functionality and work from your client application to the server

Answer 28

Bulk API moves the functionality and work from your client application to the server

Question 29

Which of the following is true: The hard delete function in the Bulk API: - Is disabled by default - Allows deleted records to stay in the Recycle Bin for 15 days - Can be used only when deleting fewer than 10,000 records - Is not a recommended strategy for deleting large data volumes

Answer 29

The hard delete function in the Bulk API is disabled by default

Question 30

What is enabled for the Bulk API by default?

Answer 30

Parallel Mode

Question 31

Describe Parallel Mode within the Bulk API

Answer 31

It is enabled by default. It allows for faster loading of data by processing batches in parallel

Question 32

What are the trade-offs with respect to Parallel Mode?

Answer 32

There is a risk of lock contention. Serial mode is an alternative to Parallel mode in order to avoid lock contentions

Question 33

When should you use Parallel Mode versus Serial Mode?

Answer 33

Whenever possible, as it is a best practice.

Question 34

When should you use Serial Mode versus Parallel Mode?

Answer 34

When there is a risk of lock contention and you cannot reorganize the batches to avoid these locks.

Question 35

How can you organize data load batches to avoid risks of lock contention?

Answer 35

By organizing the data by parent Id. Suppose that you are inserting AccountTeamMember records and you have references to the same Account Id within multiple batches. You risk lock timeouts as these multiple batches process (for example in parallel) and attempt to lock the Account record at once. To avoid these lock contentions, organize your data by Account Id such that all AccountTeamMember Records referencing the same Account Id are in the same batch

Question 36

What does the Bulk API do when it encounters locks?

Answer 36

1. Waits a few seconds for the lock to be released 2. If lock is not released, the records is marked as failed 3. If there are problems acquiring locks for more than 100 records in the batch, the remainder of the batch is put back in the queue and will be tried again later. 4. When a batch is reprocessed, records that are marked as failed will not be retried. Resubmit these in a separate batch to have them processed 5. The batch will be tried again up to 10 times before the batch is marked as failed 6. As some records have succeeded, you should check the results of the data load to confirm success/error details

Question 37

With respect to data loads, any batch job that takes longer than this amount of time is suspended and returned to the queue for later processing

Answer 37

10 minutes.

Question 38

With respect to data loads, how can you optimize batch sizes?

Answer 38

All batches should run in under 10 minutes. Start with 5000 records per batch and adjust accordingly based on the processing time. If processing time is more than 5 minutes, reduce the batch size. If it takes only a few seconds, increase the batch size. And so on. If you get a timeout error, split your batches into smaller batches.