我不确定官方的dynamodb本地是否默认支持这一点,而且看起来您需要一个将csv导入dynamodb的自定义脚本,但是您可以根据需要创建一个自定义图像。例如,你可以从一个简单的
Dockerfile
使用
amazon/dynamodb-local
然后添加一个python脚本,该脚本将负责导入csv文件,因此步骤可能如下:
-
在容器中装入csv,可能在容器内部
/docker-entrypoint-initdb.d
-
创建一个entrypoint.sh脚本,将其用作容器的入口点,并检查其中是否有任何csv文件
/docker入口点initdb.d
以便将其传递给python脚本-
下面添加的代码
-它将加载到dynamodb中,例如如下所示(取自
mongodb's entrypoint
)以下内容:
for f in /docker-entrypoint-initdb.d/*; do
case "$f" in
# if csv file pass it to the python script
*.csv) echo "$0: running $f"; . "$f" ;;
*) echo "$0: ignoring $f" ;;
esac
echo
done
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
测试.CSV的内容(必须位于与Python脚本相同的文件夹中):
John,Doe
Bob,Smith
Alice,Lee
Foo,Bar
a,b
c,d
e,f
g,h
i,j
j,l
