Question: I have a string that is comma separated (they are records), for example,

```
0,CSVSO67695,97971,2014-03-05 00:00:00.000,WB-H098,1,4.99,Individual,Sales extract OK!,255.0,1,CSVSO53485,47747,2013-07-31 00:00:00.000,SJ-0194-L,10,323.94,Store,Sales extract OK!,255.0

```

and I want to parse the string and put the values into a table.
Here are the variable names:

```
ID int
SalesOrderNumber  varchar(15)
SalesOrderDetailID int
OrderDate date
ProductNumber varchar(25)
Quantity int
LineTotal money
CustomerType varchar(25)
TestData_1 varchar(50)
TestData_2 varchar(50)

```

Answer: 
This is because the amount of CPU your containers are allocated is proportional to the amount of memory you ask for.

> 
> AWS Lambda allocates CPU power proportional to the memory by using the same ratio as a general purpose Amazon EC2 instance type, such as an M3 type. For example, if you allocate 256 MB memory, your Lambda function will receive twice the CPU share than if you allocated only 128 MB.
> 
> 
> <http://docs.aws.amazon.com/lambda/latest/dg/lambda-introduction-function.html>
> 
> 
> 

M3 instances have 8 Xeon E5-2670 or Xeon E5-2670 V2 hyperthreads per 30 GB of RAM, so at that ratio, with 1.5GB of memory, you have approximately 1.5 × (8 ÷ 30) × 2.6 GHz ≅ 1 GHz of CPU. At 128 MB you have only about 1/12 of that.
When you increase the memory allocated to Lambda functions, you also get an increase in CPU power. Note that increasing memory also increase the cost.

[AWS Lambda FAQs](https://aws.amazon.com/lambda/faqs/)

Q: How are compute resources assigned to an AWS Lambda function?

In the AWS Lambda resource model, you choose the amount of memory you want for your function, and are allocated proportional CPU power and other resources. For example, choosing 256MB of memory allocates approximately twice as much CPU power to your Lambda function as requesting 128MB of memory and half as much CPU power as choosing 512MB of memory. You can set your memory in 64MB increments from 128MB to 1.5GB.