Temporality
Fauna documents are temporal. Create, update, and delete operations are assigned a transaction timestamp that maintains a document history.
With document history, you to query your database at a point in time. This facilitates event sourcing, reactive programming, and audit- and stream-oriented data architectures.
Document history
When a document is created or updated, Fauna stores a new version
of the document with the current transaction timestamp. Fauna
indexes also store the history of fields in the index terms
or
values
definitions. The result is a record of the evolution of your
database, updated as changes occur.
Fetch a document snapshot
You can use an at
expression
to run a temporal query. Temporal queries get a snapshot of one or more
documents from a previous point in time.
For example, the following query retrieves a snapshot of a document from yesterday:
let yesterday = Time.now().subtract(1, "day")
at (yesterday) { Product.byName("avocados").first() }
Document or history removal
Temporal queries work as expected when document history exists. Note that document history increases the amount of storage required for your database, and significant amounts of history can affect the performance of your queries.
If temporality is less important than billing and performance, you should use one or more of the following features to remove document history or to remove documents and their history:
Document history removal
The history_days
field defines the number of days of document history to
maintain for all documents in the collection. After the number of days
elapses, document history is removed, but the document is retained.
This feature is useful for documents that change frequently, and only the most recent versions are required. For example, a document that stores a rolling overage of some activity over the past month.
The default history_days
value of zero is appropriate for a collection that
stores counters because those are updated at a high rate. Counters that update
multiple times per second can cause enough history to be
retained to noticeably affect the performance of queries operating on the
counter.
Setting Setting |
Updating history_days
has the following behavior. If history_days
becomes
smaller, such as changing the value from 10 days to zero days, history is
truncated as of the time of the collection document update minus the new
history_days
value. History before the new history_days
setting is
inaccessible.
If history_days
becomes larger, such as changing the value from zero to 30
days, history begins accumulating as of the time of the collection document
update. After history_days
expires, history before the time of the update
to the collection becomes inaccessible.
Document removal
The ttl
document field specifies the document time-to-live.
When the ttl
timestamp is passed, the document is removed, but its
history continues to exist until the collection history_days
has
elapsed.
This feature can be useful for documents that must exist for short intervals, and you want to avoid executing maintenance queries to remove the documents.
This is particularly useful for intermediate documents involved in gathering report data. These documents must be retained during complex report preparation. After the report is generated, the documents are removed.
This feature should be used with caution because documents with ttl
set
might be removed. As such, the default ttl
is undefined,
which means the document history is retained indefinitely.
The ttl
field controls the following behavior:
-
Queries using temporality return an error if the effective query timestamp is older than a collection
history_days
value. -
Indexes don’t report document events older than the
history_days
value in the source collections.
Set a default ttl
A collection schema’s ttl_days
field defines the default retention period, in days,
for documents in the collection. When ttl_days
is set, new documents in the
collections are assigned a ttl
value based on ttl_days
and the document’s
last write.
Enable or disable ttl writes
A collection schema’s document_ttls
field controls whether you can
write to the ttl
field of the collection’s documents.
document_ttls
does not affect the ttl
of existing documents. Fauna will
continue to delete documents based on their ttl
, even if document_ttls
is
false
.
document_ttls
also does not affect the collection schema’s ttl_days
field.
If configured, ttl_days
will continue to set a ttl
on document writes, even
if document_ttls
is false
.
If the collection schema contains
field definitions,
document_ttls
defaults to false
. Otherwise, document_ttls
defaults to
true
.
Set a ttl for existing collection documents
You can update a collection’s
schema to set or change its ttl_days
value.
collection Product {
...
// Explicitly set `document_ttls` to `true`
document_ttls true
// Set default document `ttl` to timestamp + 365 days
ttl_days 365
...
}
Changing ttl_days
on an existing collection only affects:
-
New documents
-
Documents changed after
ttl_days
is set
It does not change the ttl
of existing documents.
To set the ttl
for a large set of existing documents, you can iterate through
the collection instead. You’ll likely need to use
paginate()
to perform the
update over several transactions.
// First transaction
let page = Product
.all()
.where(.ttl == null)
.paginate()
// Subsequent transactions
// let page = Set.paginate("hdWDxoq...")
let data = page.data
data.forEach(document => document.update({
// Set ttl as document timestamp + 365 days
ttl: document.ts.add(365, "days")
}))
page {
after
}
To set the ttl
for a small set of existing documents, you can create a new
collection with your desired ttl_days
value. Then copy documents you want
to update to the collection.
// Get retained documents from the ProductOld collection
let docsToCopy = ProductOld
.all()
.where(.ttl == null)
.toArray()
.map(document => Object.assign({ }, document.data))
// Adds the documents to the ProductNew collection
docsToCopy.map(data => ProductNew.create(data))
See also
See the at expression reference documentation for how to query your database at a point in time.
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