Introduction to MongoDB cursor.tailable() Method
MongoDB is an open-source document-oriented database that stores data in documents instead of tables as in traditional relational databases. The cursor.tailable()
method is used in MongoDB to obtain a cursor, which returns an iterable result set that can be used to implement features similar to “continuous listening,” where newly added data can be obtained in real-time.
Syntax
The syntax for the cursor.tailable()
method is as follows:
db.collection.find().tailable([options])
The options
parameter is a dictionary-type parameter that can be used to configure some properties of the cursor, such as timeout and cache size.
Use Cases
The cursor.tailable()
method is typically used to monitor databases in real-time. For example, in a logging system, this method can be used to obtain newly added log data in real-time. Additionally, the cursor.tailable()
method can also be used to implement some asynchronous processing logic, such as asynchronous processing of data in the database.
Examples
The following are two examples of the cursor.tailable()
method, demonstrating how to use it to obtain newly added log data and how to implement asynchronous processing logic.
Example 1: Obtain Newly Added Log Data
Suppose we have a collection named “logs” that stores some log data. Now, we need to obtain newly added log data in real-time.
First, we need to obtain a cursor, as shown in the following code:
cursor = db.logs.find((tailable = True), (await_data = True))
In the above code, tailable=True
indicates that the cursor is in tail mode, and await_data=True
indicates that the cursor will wait for data until new data is generated. Then, we can use a loop to iterate through the cursor and obtain the newly added data:
while cursor.alive:
try:
document = next(cursor)
print(document)
except StopIteration:
time.sleep(1)
In the above code, cursor.alive
is used to determine whether the cursor is still alive. If the cursor is invalid, the loop will stop. next(cursor)
is used to obtain the next document in the cursor.
Example 2: Implement Asynchronous Processing Logic
Suppose we have a collection named “tasks” that stores some tasks that need to be processed asynchronously. Now, we need to implement an asynchronous processing logic that can immediately process new tasks as they arrive.
First, we need to obtain a cursor, as shown in the following code:
cursor = db.tasks.find((tailable = True), (await_data = True))
In the above code, tailable=True
indicates that the cursor is in tail mode, and await_data=True
indicates that the cursor will wait for data until new data is generated. Then, we can use a loop to iterate through the cursor and obtain the newly added tasks:
while True:
try:
doc = cursor.next()
print(doc)
except StopIteration:
time.sleep(1)
In the loop, we use the cursor.next()
method to obtain the next document. If there is no new document, a StopIteration exception will be raised. Therefore, we catch the StopIteration exception, pause for one second using the time.sleep(1)
method, and then continue the loop to wait for a new document.
Conclusion
This article introduced the cursor.tailable()
method of MongoDB, which allows us to use tail mode to obtain newly added documents. When using the tailable()
method, it is important to note that the collection must use capped collection and the tailable=True
and await_data=True
parameters must be specified when using the cursor. When iterating over newly added documents using the cursor, use a loop and cursor.next()
method to retrieve the documents. If there are no new documents, catch the StopIteration exception and pause for a period of time.