DELETE
This article provides an overview and how-to instructions for deleting documents using the EVICT
DQL operation.
Evicting Data
The EVICT method, once invoked, immediately removes the specified document from the local Ditto store, making it inaccessible by local queries.
For complete DQL syntax, see EVICT.
Although the document you evicted is removed from the local Ditto store, the document stored within remote Ditto stores persists.
To prevent the evicted data from reappearing on the screen in a single flicker, make sure to stop subscriptions before you call EVICT; otherwise, the subscription remains active and even if you reset the data in your end-user environment, the evicted data momentarily reappears.
Evicting Multiple Documents in a Collection
The EVICT
operation functions based on a condition, allowing updates to multiple documents simultaneously.
For example, the following snippet, once executed, purges all blue
cars stored in the local Ditto store.
Referencing Previously Evicted Documents
Once removed, you can reference the evicted document using the mutatedDocumentIDs
method on the result
.
Using Evict with Sync Subscriptions
To clear documents with active subscriptions, you must first cancel the relevant subscription before calling the EVICT
method.
You must manage subscriptions and evictions carefully.
If subscriptions are not properly managed prior to executing evictions, you may inadvertently disrupt the intended state, resulting in inconsistencies and unexpected behavior. For instance, the eviction process failing and the document persisting in the local Ditto store.
For example, if you have an active subscription for fetching ‘blue’ cars and you subsequently evict the document with the ID ‘123456’ that matches the replication query, connected peers reinstate it in your local Ditto store. In other words, the document does not clear and remains available in the local Ditto store.
Timing Subscriptions and Evictions
The frequency for removing locally stored documents depends on your app’s use case:
- To avoid the risk of depleting local storage capacity, consider evicting data frequently, such as once per day (if not more).
- To enhance offline datastore resiliency, you can implement app logic that allows your end users to choose which data to evict from their environments.
In addition, take a balanced approach when using the Subscribe and Evict methods. Consider the advantages and drawbacks of each method and use them as appropriate for specific needs and requirements.
Key considerations for using Subscription and Eviction methods include:
- Use Subscribe to sync more data across connected peers in the mesh; however, be mindful of potential increased network usage, which may degrade sync performance.
- Use Evict to manage local storage capacity and improve performance by routinely purging data stored locally.
Coordinating Evictions
Deleting Attachments
Unlike documents, attachments cannot be explicitly deleted on their own. Instead, you modify the document containing the attachment token referencing it.
Attachments currently can only be deleted by way of garbage collection.
Unlike documents, attachments cannot be explicitly deleted on their own. Instead, you modify the document containing the attachment token referencing it.
The following table provides an overview of the various ways you can indirectly delete attachments:
Approach | Description |
---|---|
UPDATE | Update the document to remove the associated attachment token. |
EVICT | Delete the entire document, including the associated attachment token, from the Ditto store. |
The storage mechanism Small Peers use to store data, including blob data, depends on the platform:
- If running in the browser or a server-based system, data is stored in its Random Access Memory (RAM).
- If running on a mobile device like an iPhone, data is stored on its local filesystem.
Soft-Delete Pattern
If you need a data recovery option, instead of permanently removing the data from the local Ditto store like EVICT
, opt for a soft-delete pattern.
A soft-delete pattern is a way to flag data as inactive while retaining it for various requirements, such as archival evidence, reference integrity, prevention of potential data loss due to end-user error, and so on.
Adding a Soft-Delete Flag
To add a soft-delete pattern, set the isArchived
field value to true
:
Querying Non-Archived Documents
To query to monitor documents that are NOT
* *archived, establish a live query where isArchived
is set to false
, and then construct your live query callback.
It’s likely that the isArchived
field is set lazily (i.e. has no value until it is true
), so you can use the coalesce()
function to automatically return false
if the value is unset.
The following code demonstrates searching for documents that are unarchived:
Removing Soft-Delete Flag
To remove the flag and reactivate the document, set the isArchived
field to false
:
Considerations
To mitigate the risk of memory leaks, performance degradation, crashes, data loss, and, if applicable, reduced battery life, it is critical that you implement a thoughtful memory management strategy in your app.
Depending on your use case, use either the Evict method or apply the soft-delete pattern to implement tools to help optimize memory usage in your app.
When planning your approach to memory management in your app, use the following criteria to help you during the decision-making process:
Consideration | Recommendation |
---|---|
Access frequency and relevance | Ensure memory is allocated only to the most relevant and frequently accessed documents by establishing an automatic process that evicts documents that are: - Accessed less frequently - No longer relevant or needed |
Time-based data | Establish an automatic process to evict or remove time-based data older than a minimum of seven days. (Until expired, time-based data remains accessible by way of local queries.) |
Permanent data loss | If documents are evicted from a local peer and don’t exist on any other peer this data is lost and is unrecoverable. |
Access Frequency and Relevance Considerations
In peer-to-peer system design, there are technical tradeoffs between the amount of data synced across peers and the timeliness of access to synced data:
- The greater the amount of data synced, the more timely offline read access becomes. That is, database resilience in offline scenarios increases when more documents are being synced across distributed peers.
- The fewer the number of documents replicated, the less the likelihood that peer devices run out of disk space and experience memory leaks, and the performance of the peer-to-peer mesh network that interconnects them degrades.
For considerations on using the Evict and Subscribe methods, see Timing Subscriptions and Evictions.
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