Time-series collections in MongoDB - Step-by-Step Execution

Concept Flow - Time-series collections

Create time-series collection

↓

Insert data with timestamp

↓

MongoDB stores data optimized

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Query data by time range

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Return matching time-series documents

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End

This flow shows creating a time-series collection, inserting timestamped data, storing it efficiently, querying by time, and returning results.

Execution Sample

MongoDB

db.createCollection("temps", {
  timeseries: { timeField: "timestamp" }
});
db.temps.insertMany([
  { timestamp: ISODate("2024-06-01T10:00:00Z"), temp: 22 },
  { timestamp: ISODate("2024-06-01T11:00:00Z"), temp: 23 }
]);
db.temps.find({ timestamp: { $gte: ISODate("2024-06-01T10:30:00Z") } })

Creates a time-series collection, inserts two temperature records with timestamps, then queries for records after 10:30.

Execution Table

Step	Action	Input/Condition	Result/Output
1	Create collection	timeseries with timeField 'timestamp'	Collection 'temps' created as time-series
2	Insert document	{timestamp: 2024-06-01T10:00:00Z, temp: 22}	Document stored in 'temps'
3	Insert document	{timestamp: 2024-06-01T11:00:00Z, temp: 23}	Document stored in 'temps'
4	Query documents	timestamp >= 2024-06-01T10:30:00Z	Returns document with timestamp 11:00
5	Query documents	timestamp >= 2024-06-01T10:30:00Z	Does not return document with timestamp 10:00
6	End	No more steps	Query complete, results returned

💡 Query ends after returning all documents matching the time condition

Variable Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	Final
temps collection	empty	1 document (10:00)	2 documents (10:00, 11:00)	2 documents (10:00, 11:00)	2 documents (10:00, 11:00)
query result	none	none	none	1 document (11:00)	1 document (11:00)

Key Moments - 2 Insights

Why does the query only return the document with timestamp 11:00 and not 10:00?

Because the query condition is timestamp >= 2024-06-01T10:30:00Z, so only documents with timestamp at or after 10:30 are returned (see execution_table rows 4 and 5).

What is special about creating a time-series collection compared to a normal collection?

A time-series collection is optimized to store and query data with a timeField, improving performance for time-based queries (see execution_table row 1).

Visual Quiz - 3 Questions

Look at the execution_table, what is the state of the 'temps collection' after step 3?

A 2 documents with timestamps 10:00 and 11:00

B 1 document with timestamp 10:00

C Empty collection

D 3 documents with timestamps 10:00, 11:00, and 12:00

💡 Hint

Check variable_tracker row for 'temps collection' after Step 3

At which step does the query return documents matching the time condition?

A Step 2

B Step 4

C Step 1

D Step 3

💡 Hint

Look at execution_table rows describing query actions and results

If the query condition changed to timestamp >= 2024-06-01T09:00:00Z, what would happen?

A No documents would be returned

B Only the document with timestamp 11:00 would be returned

C Both documents with timestamps 10:00 and 11:00 would be returned

D Only the document with timestamp 10:00 would be returned

💡 Hint

Consider the timestamps of inserted documents and the new query condition

Concept Snapshot

Time-series collections store data with a timestamp field.
Create with db.createCollection and specify timeseries and timeField.
Insert documents with timestamps.
Query by time ranges efficiently.
MongoDB optimizes storage and queries for time-series data.

Full Transcript

This visual execution trace shows how to create a MongoDB time-series collection named 'temps' with a timeField called 'timestamp'. Two documents with timestamps 10:00 and 11:00 are inserted. A query is run to find documents with timestamp greater or equal to 10:30. The query returns only the document with timestamp 11:00 because the other document is before 10:30. The variable tracker shows the collection state after each step and the query result. Key moments clarify why only some documents match the query and what makes time-series collections special. The quiz tests understanding of collection state and query results at different steps.