Table of Contents

Bucket

AIStore uses the popular and well-known bucket abstraction, originally (likely) introduced by Amazon S3.

Similar to S3, AIS bucket is a container for objects.

An object, in turn, is a file and a metadata that describes that object and normally includes: checksum, version, references to copies (replicas), size, last access time, source bucket (if object’s origin is a Cloud bucket), custom user-defined attributes, and more.

AIS is a flat <bucket-name>/<object-name> storage hierarchy where named buckets store user datasets.

In addition, each AIS bucket is a point of applying (per-bucket) management policies: checksumming, versioning, erasure coding, mirroring, LRU eviction, checksum and/or version validation, and more.

AIS buckets contain user data performing the same function as, for instance:

In addition, AIS supports multiple storage backends including itself:

Supported Backends

All the supported storage services equally apply to all storage backends with only a few exceptions. The following table summarizes them.

Kind Description Supported Storage Services
AIS buckets buckets that are not 3rd party backend-based. AIS buckets store user objects and support user-specified bucket properties (e.g., 3 copies). Unlike remote buckets, ais buckets can be created through the RESTful API. Similar to remote buckets, ais buckets are distributed and balanced, content-wise, across the entire AIS cluster. Checksumming, LRU (advanced usage), Erasure Coding, Local Mirroring and Load Balancing
remote buckets When AIS is deployed as fast tier, buckets in the cloud storage can be viewed and accessed through the RESTful API in AIS, in the exact same way as ais buckets. When this happens, AIS creates local instances of said buckets which then serves as a cache. These are referred to as 3rd party backend-based buckets. Checksumming, LRU, Erasure Coding, Local mirroring and load balancing

3rd party backend-based and AIS buckets support the same API with a few documented exceptions. Remote buckets can be evicted from AIS. AIS buckets are the only buckets that can be created, renamed, and deleted via the RESTful API.

Default Bucket Properties

By default, created buckets inherit their properties from the cluster-wide global configuration. Similar to other types of cluster-wide metadata, global configuration (also referred to as “cluster configuration”) is protected (versioned, checksummed) and replicated across the entire cluster.

Important:

  • Bucket properties can be changed at any time via api.SetBucketProps.
  • In addition, api.CreateBucket allows to specify (non-default) properties at bucket creation time.
  • Inherited defaults include (but are not limited to) checksum, LRU, versioning, n-way mirroring, and erasure-coding configurations.
  • By default, LRU is disabled for AIS (ais://) buckets.

Use api.SetBucketProps to enable LRU-based eviction on any given ais bucket (or, vice versa, disable LRU on any specific remote bucket) of your choice.

Bucket creation operation allows to override the inherited defaults, which include:

Configuration section References
Backend Backend Provider
Checksum Supported Checksums and Brief Theory of Operations
LRU Storage Services: LRU
N-way mirror Storage Services: n-way mirror
Versioning ---
Access Bucket Access Attributes
Erasure Coding Storage Services: erasure coding
Metadata Persistence ---

Example specifying (non-default) bucket properties at creation time:

$ ais create ais://abc --props="lru.enabled=false mirror.enabled=true mirror.copies=4"

# or, same using JSON:
$ ais create ais://abc --props='{"lru": {"enabled": false}, "mirror": {"enabled": true, "copies": 4}}'

Inherited Bucket Properties and LRU

  1. LRU eviction triggers automatically when the percentage of used capacity exceeds configured (“high”) watermark lru.highwm. The latter is part of bucket configuration and one of the many bucket properties that can be individually configured.
  2. By default, lru.highwm = 90% of total storage space.
  3. Another important knob is lru.enabled that defines whether a given bucket can be a subject of LRU eviction in the first place.
  4. By default, these two and all the other knobs are inherited by a newly created bucket from default (global, cluster-wide) configuration.
  5. However, those inherited defaults can be changed - overridden - both at bucket creation time, and at any later time.

Going back to LRU, it can be disabled (or enabled) on a per bucket basis.

Prior to the version 3.8, LRU eviction was by default globally enabled. Starting v3.8, LRU is enabled by default only for remote buckets.

AIS buckets that have remote backends are, by definition, remote buckets. See next section for details.

In summary, starting v3.8, a newly created AIS bucket inherits default configuration that makes the bucket non-evictable.

Useful CLI commands include:

# CLI to conveniently _toggle_ LRU eviction on and off on a per-bucket basis:
$ ais bucket lru ...

# Reset bucket properties to cluster-wide defaults:
$ ais bucket props reset ...

# Evict any given bucket based on a user-defined _template_.
# The command is one of the many supported _multi-object_ operations that run asynchronously
# and handle arbitrary (list, range, prefix)-defined templates.
$ ais bucket evict ...

See also:

Backend Provider

Backend Provider is an abstraction, and, simultaneously, an API-supported option that allows to delineate between “remote” and “local” buckets with respect to a given (any given) AIS cluster. For complete definition and details, please refer to the backend provider document.

Backend provider is realized as an optional parameter in the GET, PUT, APPEND, DELETE and Range/List operations with supported enumerated values that include:

  • ais - for AIS buckets
  • aws or s3 - for Amazon S3 buckets
  • azure or az - for Microsoft Azure Blob Storage buckets
  • gcp or gs - for Google Cloud Storage buckets
  • hdfs - for Hadoop/HDFS clusters
  • ht - for HTTP(S) based datasets

For API reference, please refer to the RESTful API and examples. The rest of this document serves to further explain features and concepts specific to storage buckets.

AIS Bucket

AIS buckets are the AIStore-own distributed buckets that are not associated with any 3rd party Cloud.

The RESTful API can be used to create, copy, rename and, destroy ais buckets.

New ais buckets must be given a unique name that does not duplicate any existing ais bucket.

If you are going to use an AIS bucket as an S3-compatible one, consider changing the bucket’s checksum to MD5. For details, see S3 compatibility.

CLI: create, rename and, destroy ais bucket

To create an ais bucket with the name yt8m, rename it to yt8m_extended and delete it, run:

$ ais create ais://yt8m
$ ais bucket mv ais://yt8m ais://yt8m_extended
$ ais bucket rm ais://yt8m_extended

Please note that rename bucket is not an instant operation, especially if the bucket contains data. Follow the rename command tips to monitor when the operation completes.

CLI: specifying and listing remote buckets

To list absolutely all buckets that your AIS cluster has access to, run ais ls.

To lists all remote (and only remote) buckets, use: ais ls @. For example:

$ ais ls @

AIS Buckets (1)
  ais://@U-0MEX8oYt/abc
GCP Buckets (7)
  gcp://lpr-foo
  gcp://lpr-bar
  ... (another 5 buckets omitted)

This example assumes that there’s a remote AIS cluster identified by its UUID U-0MEX8oYt and previously attached to the “local” one.

Notice the naming notiation reference remote AIS buckets: prefix @ in the full bucket name indicates remote cluster’s UUIDs.

Complete bucket naming specification includes bucket name, backend provider and namespace (which in turn includes UUID and optional sub-name, etc.). The spec can be found in this source.

And here are CLI examples of listing buckets by a given provider:

List Google buckets:

$ ais ls gs://
# or, same:
$ ais ls gs:

GCP Buckets (7)
  gcp://lpr-foo
  gcp://lpr-bar
  ...

List AIS buckets:

$ ais ls ais://
# or, same:
$ ais ls ais:

List remote AIS buckets:

$ ais ls ais://@

CLI: working with remote AIS cluster

AIS clusters can be attached to each other, thus forming a global (and globally accessible) namespace of all individually hosted datasets. For background and details on AIS multi-clustering, please refer to this document.

The following example creates an attachment between two clusters, lists all remote buckets, and then list objects in one of those remote buckets (see comments inline):

$ # Attach remote AIS cluster and assign it an alias `teamZ` (for convenience and for future reference):
$ ais cluster attach teamZ=http://cluster.ais.org:51080
Remote cluster (teamZ=http://cluster.ais.org:51080) successfully attached
$
$ # The cluster at http://cluster.ais.org:51080 is now persistently attached:
$ ais show remote-cluster
UUID      URL                            Alias     Primary      Smap   Targets  Online
MCBgkFqp  http://cluster.ais.org:51080   teamZ     p[primary]   v317   10       yes
$
$ # List all buckets in all remote clusters
$ # Notice the syntax: by convention, we use `@` to prefix remote cluster UUIDs, and so
$ # `ais://@` translates as "AIS backend provider, any remote cluster"
$
$ ais ls ais://@
AIS Buckets (4)
	  ais://@MCBgkFqp/imagenet
	  ais://@MCBgkFqp/coco
	  ais://@MCBgkFqp/imagenet-augmented
	  ais://@MCBgkFqp/imagenet-inflated
$
$ # List all buckets in the remote cluster with UUID = MCBgkFqp
$ # Notice the syntax: `ais://@some-string` translates as "remote AIS cluster with alias or UUID equal some-string"
$
$ ais ls ais://@MCBgkFqp
AIS Buckets (4)
	  ais://@MCBgkFqp/imagenet
	  ais://@MCBgkFqp/coco
	  ais://@MCBgkFqp/imagenet-augmented
	  ais://@MCBgkFqp/imagenet-inflated
$
$ # List all buckets with name matching the regex pattern "tes*"
$ ais ls --regex "tes*"
AWS Buckets (3)
  aws://test1
  aws://test2
  aws://test2
$
$ # We can conveniently keep using our previously selected alias for the remote cluster -
$ # The following lists selected remote bucket using the cluster's alias:
$ ais ls ais://@teamZ/imagenet-augmented
NAME              SIZE
train-001.tgz     153.52KiB
train-002.tgz     136.44KiB
...
$
$ # The same, but this time using the cluster's UUID:
$ ais ls ais://@MCBgkFqp/imagenet-augmented
NAME              SIZE
train-001.tgz     153.52KiB
train-002.tgz     136.44KiB
...

Remote Bucket

Remote buckets are buckets that use 3rd party storage (AWS/GCP/Azure or HDFS) when AIS is deployed as fast tier. Any reference to “Cloud buckets” refer to remote buckets that use a public cloud bucket as their backend (i.e. AWS/GCP/Azure, but not HDFS).

By default, AIS does not keep track of the remote buckets in its configuration map. However, if users modify the properties of the remote bucket, AIS will then keep track.

Public Cloud Buckets

Public Google Storage supports limited access to its data. If AIS cluster is deployed with Google Cloud enabled (Google Storage is selected as 3rd party Backend provider when deploying an AIS cluster), it allows a few operations without providing credentials: HEAD a bucket, list bucket objects, GET an object, and HEAD an object. The example shows accessing a private GCP bucket and a public GCP one without user authorization.

$ # Listing objects of a private bucket
$ ais ls gs://ais-ic
Bucket "gcp://ais-ic" does not exist
$
$ # Listing a public bucket
$ ais ls gs://pub-images --limit 3
NAME                         SIZE
images-shard.ipynb           101.94KiB
images-train-000000.tar      964.77MiB
images-train-000001.tar      964.74MiB

Even if an AIS cluster is deployed without Cloud support, it is still possible to access public GCP and AWS buckets. Run downloader to copy data from a public Cloud bucket to an AIS bucket and then use the AIS bucket. Example shows how to download data from public Google storage:

$ ais create ais://images
"ais://images" bucket created
$ ais start download "gs://pub-images/images-train-{000000..000001}.tar" ais://images/
Z8WkHxwIrr
Run `ais show job download Z8WkHxwIrr` to monitor the progress of downloading.
$ ais wait download Z8WkHxwIrr # or, same: ais wait Z8WkHxwIrr
$ ais ls ais://images
NAME                         SIZE
images-train-000000.tar      964.77MiB
images-train-000001.tar      964.74MiB

Job starting, stopping (i.e., aborting), and monitoring commands all have equivalent shorter versions. For instance ais start download can be expressed as ais start download, while ais wait copy-bucket Z8WkHxwIrr is the same as ais wait Z8WkHxwIrr.

Remote AIS cluster

AIS cluster can be attached to another one which provides immediate capability for one cluster to “see” and transparently access the other’s buckets and objects.

The functionality is termed global namespace and is further described in the backend providers readme.

To support global namespace, bucket names include @-prefixed cluster UUID. For remote AIS clusters, remote UUID and remote aliases can be used interchangeably.

For example, ais://@remais/abc would translate as AIS backend provider, where remote cluster would have remais alias.

Example working with remote AIS cluster (as well as easy-to-use scripts) can be found at:

Public HTTP(S) Dataset

It is standard in machine learning community to publish datasets in public domains, so they can be accessed by everyone. AIStore has integrated tools like downloader which can help in downloading those large datasets straight into provided AIS bucket. However, sometimes using such tools is not a feasible solution.

For other cases AIStore has ability to act as a reverese-proxy when accessing any URL. This enables downloading any HTTP(S) based content into AIStore cluster. Assuming that proxy is listening on localhost:8080, one can use it as reverse-proxy to download http://storage.googleapis.com/pub-images/images-train-000000.tar shard into AIS cluster:

$ curl -sL --max-redirs 3 -x localhost:8080 --noproxy "$(curl -s localhost:8080/v1/cluster?what=target_ips)" \
  -X GET "http://storage.googleapis.com/minikube/minikube-0.6.iso.sha256" \
  > /dev/null

Alternatively, an object can also be downloaded using the get and cat CLI commands.

$ ais get http://storage.googleapis.com/minikube/minikube-0.7.iso.sha256 minikube-0.7.iso.sha256

This will cache shard object inside the AIStore cluster. We can confirm this by listing available buckets and checking the content:

$ ais ls
AIS Buckets (1)
  ais://local-bck
AWS Buckets (1)
  aws://ais-test
HTTP(S) Buckets (1)
  ht://ZDdhNTYxZTkyMzhkNjk3NA (http://storage.googleapis.com/minikube/)
$ ais ls ht://ZDdhNTYxZTkyMzhkNjk3NA
NAME                                 SIZE
minikube-0.6.iso.sha256	              65B

Now, when the object is accessed again, it will be served from AIStore cluster and will not be re-downloaded from HTTP(S) source.

Under the hood, AIStore remembers the object’s source URL and associates the bucket with this URL. In our example, bucket ht://ZDdhNTYxZTkyMzhkNjk3NA will be associated with http://storage.googleapis.com/minikube/ URL. Therefore, we can interchangeably use the associated URL for listing the bucket as show below.

$ ais ls http://storage.googleapis.com/minikube
NAME                                  SIZE
minikube-0.6.iso.sha256	              65B

Note that only the last part (minikube-0.6.iso.sha256) of the URL is treated as the object name.

Such connection between bucket and URL allows downloading content without providing URL again:

$ ais object cat ht://ZDdhNTYxZTkyMzhkNjk3NA/minikube-0.7.iso.sha256 > /dev/null # cache another object
$ ais ls ht://ZDdhNTYxZTkyMzhkNjk3NA
NAME                     SIZE
minikube-0.6.iso.sha256  65B
minikube-0.7.iso.sha256  65B

Prefetch/Evict Objects

Objects within remote buckets are automatically fetched into storage targets when accessed through AIS and are evicted based on the monitored capacity and configurable high/low watermarks when LRU is enabled.

The RESTful API can be used to manually fetch a group of objects from the remote bucket (called prefetch) into storage targets or to remove them from AIS (called evict).

Objects are prefetched or evicted using List/Range Operations.

For example, to use a list operation to prefetch ‘o1’, ‘o2’, and, ‘o3’ from Amazon S3 remote bucket abc, run:

$ ais start prefetch aws://abc --list o1,o2,o3

To use a range operation to evict the 1000th to 2000th objects in the remote bucket abc from AIS, which names begin with the prefix __tst/test-, run:

$ ais bucket evict aws://abc --template "__tst/test-{1000..2000}"

Evict Remote Bucket

Before a remote bucket is accessed through AIS, the cluster has no awareness of the bucket.

Once there is a request to access the bucket, or a request to change the bucket’s properties (see set bucket props in REST API), then the AIS cluster starts keeping track of the bucket.

In an evict bucket operation, AIS will remove all traces of the remote bucket within the AIS cluster. This effectively resets the AIS cluster to the point before any requests to the bucket have been made. This does not affect the objects stored within the remote bucket.

For example, to evict abc remote bucket from the AIS cluster, run:

$ ais bucket evict aws://abc

Note: When an HDFS bucket is evicted, AIS will only delete objects stored in the cluster. AIS will retain the bucket’s metadata to allow the bucket to re-register later. This behavior can be applied to other remote buckets by using the --keep-md flag with ais bucket evict.

Backend Bucket

So far, we have covered AIS and remote buckets. These abstractions are sufficient for almost all use cases. But there are times when we would like to download objects from an existing remote bucket and then make use of the features available only for AIS buckets.

One way of accomplishing that could be:

  1. Prefetch cloud objects.
  2. Create AIS bucket.
  3. Use the bucket-copying API or CLI to copy over the objects from the remote bucket to the newly created AIS bucket.

However, the extra-copying involved may prove to be time and/or space consuming. Hence, AIS-supported capability to establish an ad-hoc 1-to-1 relationship between a given AIS bucket and an existing cloud (backend).

As aside, the term “backend” - something that is on the back, usually far (or farther) away - is often used for data redundancy, data caching, and/or data sharing. AIS backend bucket allows to achieve all of the above.

For example:

$ ais create abc
"abc" bucket created
$ ais bucket props set ais://abc backend_bck=gcp://xyz
Bucket props successfully updated

After that, you can access all objects from gcp://xyz via ais://abc. On-demand persistent caching (from the gcp://xyz) becomes then automatically available, as well as all other AIS-supported storage services configurable on a per-bucket basis.

For example:

$ ais ls gcp://xyz
NAME		 SIZE		 VERSION
shard-0.tar	 2.50KiB	 1
shard-1.tar	 2.50KiB	 1
$ ais ls ais://abc
NAME		 SIZE		 VERSION
shard-0.tar	 2.50KiB	 1
shard-1.tar	 2.50KiB	 1
$ ais get ais://abc/shard-0.tar /dev/null # cache/prefetch cloud object
"shard-0.tar" has the size 2.50KiB (2560 B)
$ ais ls ais://abc --cached
NAME		 SIZE		 VERSION
shard-0.tar	 2.50KiB	 1
$ ais bucket props set ais://abc backend_bck=none # disconnect backend bucket
Bucket props successfully updated
$ ais ls ais://abc
NAME		 SIZE		 VERSION
shard-0.tar	 2.50KiB	 1

For more examples please refer to CLI docs.

Bucket Properties

The full list of bucket properties are:

Bucket Property JSON Description Fields
Provider provider “ais”, “aws”, “azure”, “gcp”, “hdfs” or “ht” "provider": "ais"/"aws"/"azure"/"gcp"/"hdfs"/"ht"
Cksum checksum Please refer to Supported Checksums and Brief Theory of Operations  
LRU lru Configuration for LRU. lowwm and highwm is the used capacity low-watermark and high-watermark (% of total local storage capacity) respectively. out_of_space if exceeded, the target starts failing new PUTs and keeps failing them until its local used-cap gets back below highwm. atime_cache_max represents the maximum number of entries. dont_evict_time denotes the period of time during which eviction of an object is forbidden [atime, atime + dont_evict_time]. capacity_upd_time denotes the frequency at which AIStore updates local capacity utilization. enabled LRU will only run when set to true. "lru": { "lowwm": int64, "highwm": int64, "out_of_space": int64, "atime_cache_max": int64, "dont_evict_time": "120m", "capacity_upd_time": "10m", "enabled": bool }
Mirror mirror Configuration for Mirroring. copies represents the number of local copies. burst_buffer represents channel buffer size. enabled will only generate local copies when set to true. "mirror": { "copies": int64, "burst_buffer": int64, "enabled": bool }
EC ec Configuration for erasure coding. objsize_limit is the limit in which objects below this size are replicated instead of EC’ed. data_slices represents the number of data slices. parity_slices represents the number of parity slices/replicas. enabled represents if EC is enabled. "ec": { "objsize_limit": int64, "data_slices": int, "parity_slices": int, "enabled": bool }
Versioning versioning Configuration for object versioning support where enabled represents if object versioning is enabled for a bucket. For remote bucket versioning must be enabled in the corresponding backend (e.g. Amazon S3). validate_warm_get: determines if the object’s version is checked "versioning": { "enabled": true, "validate_warm_get": false }
AccessAttrs access Bucket access attributes. Default value is 0 - full access "access": "0"
BID bid Readonly property: unique bucket ID "bid": "10e45"
Created created Readonly property: bucket creation date, in nanoseconds(Unix time) "created": "1546300800000000000"

CLI examples: listing and setting bucket properties

List bucket properties

$ ais show bucket mybucket
...
$
$ # Or, the same to get output in a (raw) JSON form:
$ ais show bucket mybucket --json
...

Enable erasure coding on a bucket

$ ais bucket props mybucket ec.enabled=true

Enable object versioning and then list updated bucket properties

$ ais bucket props mybucket versioning.enabled=true
$ ais show bucket mybucket
...

Bucket Access Attributes

Bucket access is controlled by a single 64-bit access value in the Bucket Properties structure, whereby its bits have the following mapping as far as allowed (or denied) operations:

Operation Bit Mask
GET 0x1
HEAD 0x2
PUT, APPEND 0x4
Cold GET 0x8
DELETE 0x16

For instance, to make bucket abc read-only, execute the following AIS CLI command:

$ ais bucket props abc 'access=ro'

The same expressed via curl will look as follows:

$ curl -i -X PATCH  -H 'Content-Type: application/json' -d '{"action": "set-bprops", "value": {"access": 18446744073709551587}}' http://localhost:8080/v1/buckets/abc

18446744073709551587 = 0xffffffffffffffe3 = 0xffffffffffffffff ^ (4|8|16)

List Objects

ListObjects API returns a page of object names and, optionally, their properties (including sizes, access time, checksums, and more), in addition to a token that serves as a cursor, or a marker for the next page retrieval.

When a cluster is rebalancing, the returned list of objects can be incomplete due to objects are being migrated. The returned result has non-zero value(the least significant bit is set to 1) to indicate that the list was generated when the cluster was unstable. To get the correct list, either re-request the list after the rebalance ends or read the list with the option SelectMisplaced enabled. In the latter case, the list may contain duplicated entries.

When using proxy cache (experimental) immutability of a bucket is assumed between subsequent ListObjects request. If a bucket has been updated after ListObjects request, a user should call ListObjectsInvalidateCache API to get correct ListObjects results. This is the temporary requirement and will be removed in next AIS versions.

List Options

The properties-and-options specifier must be a JSON-encoded structure, for instance {"props": "size"} (see examples). An empty structure {} results in getting just the names of the objects (from the specified bucket) with no other metadata.

Property/Option Description Value
uuid ID of the list objects operation After initial request to list objects the uuid is returned and should be used for subsequent requests. The ID ensures integrity between next requests.
pagesize The maximum number of object names returned in response For AIS buckets default value is 10000. For remote buckets this value varies as each provider has it’s own maximal page size.
props The properties of the object to return A comma-separated string containing any combination of: name,size,version,checksum,atime,location,copies,ec,status (if not specified, props are set to name,size,version,checksum,atime). 1
prefix The prefix which all returned objects must have For example, prefix = "my/directory/structure/" will include object object_name = "my/directory/structure/object1.txt" but will not object_name = "my/directory/object2.txt"
start_after Name of the object after which the listing should start For example, start_after = "baa" will include object object_name = "caa" but will not object_name = "ba" nor object_name = "aab".
continuation_token The token identifying the next page to retrieve Returned in the ContinuationToken field from a call to ListObjects that does not retrieve all keys. When the last key is retrieved, ContinuationToken will be the empty string.
time_format The standard by which times should be formatted Any of the following golang time constants: RFC822, Stamp, StampMilli, RFC822Z, RFC1123, RFC1123Z, RFC3339. The default is RFC822.
flags Advanced filter options A bit field of ListObjsMsg extended flags.
[experimental] use_cache Enables caching With this option enabled, subsequent requests to list objects for the given bucket will be served from cache without traversing disks. For now implementation is limited to caching results for buckets which content doesn’t change, otherwise the cache will be in stale state.

ListObjsMsg extended flags:

Name Value Description
SelectCached 1 For remote buckets only: return only objects that are cached on AIS drives, i.e. objects that can be read without accessing to the Cloud
SelectMisplaced 2 Include objects that are on incorrect target or mountpath
SelectDeleted 4 Include objects marked as deleted
SelectArchDir 8 If an object is an archive, include its content into object list
SelectOnlyNames 16 Do not retrieve object attributes for faster bucket listing. In this mode, all fields of the response, except object names and statuses, are empty

We say that “an object is cached” to indicate two separate things:

  • The object was originally downloaded from a remote bucket, bucket in a remote AIS cluster, or an HTTP(s) based dataset;
  • The object is stored in the AIS cluster.

In other words, the term “cached” is simply a shortcut to indicate the object’s immediate availability without the need to go and check the object’s original location. Being “cached” does not have any implications on object’s persistence: “cached” objects, similar to those objects that originated in a given AIS cluster, are stored with arbitrary (per bucket configurable) levels of redundancy, etc. In short, the same storage policies apply to “cached” and “non-cached”.

Note that the list generated with SelectMisplaced option may have duplicated entries. E.g, after rebalance the list can contain two entries for the same object: a misplaced one (from original location) and real one (from the new location).

1) The objects that exist in the Cloud but are not present in the AIStore cache will have their atime property empty (""). The atime (access time) property is supported for the objects that are present in the AIStore cache. ↩

List result

The result may contain all bucket objects(if a bucket is small) or only the current page. The struct includes fields:

Field JSON Value Description
UUID uuid Unique ID of the listing operation. Pass it to all consecutive list requests to read the next page of objects. If UUID is empty, the server starts listing objects from the first page
Entries entries A page of objects and their properties
ContinuationToken continuation_token The token to request the next page of objects. Empty value means that it is the last page
Flags flags Extra information - a bit-mask field. 0x0001 bit indicates that a rebalance was running at the time the list was generated

[experimental] Query Objects

QueryObjects API is extension of list objects. Alongside listing names and properties of the objects, it also allows filtering and selecting specific sets of objects.

At the high level, the idea is that a proxy dispatches a request to targets which produce output that is returned and combined by the proxy.

(Proxy combines and sorts the outputs returned by all targets)

When a target receives a request from the proxy, it traverses disks applying the specified filters and selections.

(Objects marked green supposedly pass all the filtering and selection, whereas red objects - do not)

Query Options

The options for init message describe the most important values of the query.

Property/Option Description Value
outer_select.prefix Prefix which all returned objects must have For example, prefix = "my/directory/structure/" will include object object_name = "my/directory/structure/object1.txt" but will not object_name = "my/directory/object2.txt"
outer_select.objects_source Template that object names must match to For example objects_source = "object{00..99}.tar" will include object object_name = "object49.tar" but will not object_name = "object0.tgz"
inner_select.props Properties of objects to return A comma-separated list containing any combination of: name, size, version, checksum, atime, location, copies, ec, status.
from.bucket Bucket in which query should be executed  
where.filter Filter to apply when traversing objects Filter is recursive data structure that can describe multiple filters which should be applied.

Init message returns handle that should be used in NextQueryResults API call.