In the end I coded a Python function import_csv_to_dynamodb(table_name, csv_file_name, colunm_names, column_types) that imports a CSV into a DynamoDB table. Column names and column must be specified. It uses boto, and takes a lot of inspiration from this gist. Below is the function as well as a demo (main()) and the CSV file used. Tested on Windows 7 x64 with Python 2.7.5, but it should work on any OS that has boto and Python.
import boto
MY_ACCESS_KEY_ID = 'copy your access key ID here'
MY_SECRET_ACCESS_KEY = 'copy your secrete access key here'
def do_batch_write(items, table_name, dynamodb_table, dynamodb_conn):
'''
From https://gist.github.com/griggheo/2698152#file-gistfile1-py-L31
'''
batch_list = dynamodb_conn.new_batch_write_list()
batch_list.add_batch(dynamodb_table, puts=items)
while True:
response = dynamodb_conn.batch_write_item(batch_list)
unprocessed = response.get('UnprocessedItems', None)
if not unprocessed:
break
batch_list = dynamodb_conn.new_batch_write_list()
unprocessed_list = unprocessed[table_name]
items = []
for u in unprocessed_list:
item_attr = u['PutRequest']['Item']
item = dynamodb_table.new_item(
attrs=item_attr
)
items.append(item)
batch_list.add_batch(dynamodb_table, puts=items)
def import_csv_to_dynamodb(table_name, csv_file_name, colunm_names, column_types):
'''
Import a CSV file to a DynamoDB table
'''
dynamodb_conn = boto.connect_dynamodb(aws_access_key_id=MY_ACCESS_KEY_ID, aws_secret_access_key=MY_SECRET_ACCESS_KEY)
dynamodb_table = dynamodb_conn.get_table(table_name)
BATCH_COUNT = 2 # 25 is the maximum batch size for Amazon DynamoDB
items = []
count = 0
csv_file = open(csv_file_name, 'r')
for cur_line in csv_file:
count += 1
cur_line = cur_line.strip().split(',')
row = {}
for colunm_number, colunm_name in enumerate(colunm_names):
row[colunm_name] = column_types[colunm_number](cur_line[colunm_number])
item = dynamodb_table.new_item(
attrs=row
)
items.append(item)
if count % BATCH_COUNT == 0:
print 'batch write start ... ',
do_batch_write(items, table_name, dynamodb_table, dynamodb_conn)
items = []
print 'batch done! (row number: ' + str(count) + ')'
# flush remaining items, if any
if len(items) > 0:
do_batch_write(items, table_name, dynamodb_table, dynamodb_conn)
csv_file.close()
def main():
'''
Demonstration of the use of import_csv_to_dynamodb()
We assume the existence of a table named `test_persons`, with
- Last_name as primary hash key (type: string)
- First_name as primary range key (type: string)
'''
colunm_names = 'Last_name First_name'.split()
table_name = 'test_persons'
csv_file_name = 'test.csv'
column_types = [str, str]
import_csv_to_dynamodb(table_name, csv_file_name, colunm_names, column_types)
if __name__ == "__main__":
main()
#cProfile.run('main()') # if you want to do some profiling
test.csv's content (must be located in the same folder as the Python script):
John,Doe
Bob,Smith
Alice,Lee
Foo,Bar
a,b
c,d
e,f
g,h
i,j
j,l
Best Answer
For each database file (other.db) that must export tables to main.db:
Or if you want to check the generated commands:
Another method: (not so good as it does not import the primary key and column types)
First open the main database:
Then for each database containing tables to be imported: