We are going to read a text file as soon as it's uploaded in S3 and add it's
data into Dynamo DB using Lambda – Node JS.
Things we will need to do:-
1.
Create S3 bucket and Dynamodb Table.
2.
Create a role (S3 access and dynamodb access) for the
lambda function that you will be creating.
3.
Create lambda function with S3 Object creation Event
source.
4.
Test.
Before we start, just some names that you should know that I
have used in the example -
S3 bucket Name: s3-to-lambda-object-creation-01
Lambda Function Name:
s3-dynamodb-lambda-02
Dynamodb Table Name: Movies
Dynamodb Table Attributes:
Key - year,
Other Attribute - title.
Step 1:-
Before we dive into how to use lambda functions and it’s
details, we need to have an S3 bucket and a Dynamodb Table in place for the
current problem statement.
Creating these two is pretty straight forward. You can refer
the links below :-
S3 :-
Dynamodb :-
Step 2:-
Before you start creating a lambda function, you need to
assign it an Execution Role so that lambda has the permission to access S3 and
Dynamodb and make changes to them.
We will be giving S3 Access and Dynamodb Access.
We are also going to give it some policies to be able to
write logs in CloudWatch.
The policy is -
Step 3:-
Select S3 from the drop-down list.
Make sure you select Object Created option for event type.
You can enable the trigger from
now itself or you can enable it later too after creating the function.
Below the code entry type - you will have to insert your
code.
|
'use strict';
console.log('Loading function');
let aws = require('aws-sdk');
let s3 = new aws.S3({ apiVersion: '2006-03-01'
});
exports.handler = (event, context, callback)
=> {
const
bucket = event.Records[0].s3.bucket.name;
const
key = decodeURIComponent(event.Records[0].s3.object.key.replace(/\+/g, ' '));
const
params = {
Bucket:
bucket,
Key: key
};
var
docClient = new aws.DynamoDB.DocumentClient();
var
table = "Movies";
s3.getObject(params, (err, data) => {
if
(err) {
console.log(err);
const message = `Error getting object ${key} from bucket ${bucket}.
Make sure they exist and your bucket is in the same region as this
function.`;
console.log(message);
callback(message);
}
else {
//get data in the file using data.Body
var file_data=String(data.Body);
// split the data first based on the newline character and add each
line into an array
var split_data_newline= file_data.split("\n");
var final_split_data= []; // 2D array
with final split data from file
var temp_comma_split= []; // Temp array for storing ","
seperated values of each line
var i,j=0;
// interate through the array which contains full full lines as it's
element.. now take each element of that array and split using ","
// take the "," seperated items into a temp array
(temp_comma_split)
// using the second inner for loop.. iterate the temp array and add
each element of it into the 2D array (final_split_data)
for(i=0; i<split_data_newline.length; i++) {
final_split_data[i]= [];
temp_comma_split = split_data_newline[i].split(",");
for(j=0; j<temp_comma_split.length; j++) {
final_split_data[i][j]=temp_comma_split[j];
}
}
// Iterate through the final 2D array with
data to add into DB fields
for(i=0; i<final_split_data.length; i++) {
var year = final_split_data[i][0];
var title = final_split_data[i][1];
var DB_params = {
TableName:table,
Item:{
"year":
year,
"title":
title,
}
};
console.log("Adding a new item...");
docClient.put(DB_params, function(err,
data) {
if (err) {
console.error("Unable to add item. Error JSON:",
JSON.stringify(err, null, 2));
} else {
console.log("Added
item:", JSON.stringify(data, null, 2));
}
});
}
}
});
};
|
After the code, AWS will pre-populate the Handler field for
you. It is the filename.handler-function.
Step 4:-
Take the input file shown below
and upload it to your S3 bucket.
Also go to your CloudWatch Logs -
you should see a new Log Group created with the same name as your Lambda
Function. Inside the group you can see all your logs getting accumulated.
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