Before this change, attempting to upload a single file into an s3
bucket which did not have create permission gave AccessDenied: Access
Denied error when it tried to create the bucket.
This was masked until e2bf91452a was
fixed.
This fix marks the bucket as OK if a fetch on an object indicates it
is OK. This stops rclone thinking it has to create the bucket in the
first place.
Fixes#4297
Previously we had a map of pools for different chunk sizes.
In practice the mapping is not very useful and requires a lock.
Pools of size other that ChunkSize can only happen when we have a huge file (over 10k * ChunkSize).
We need to have a bunch of identically sized huge files.
In such case most likely ChunkSize should be increased.
The mapping and its lock is replaced with a single initialised pool for ChunkSize, in other cases pool is allocated and freed on per file basis.
In 5470d34740 "backend/s3: use low-level-retries as the number
of SDK retries" we switched over to using the AWS SDK low level
retries instead of rclone's low level retry logic.
This had the unfortunate attempt that retrying listings to correct XML
Syntax errors failed on non S3 backends such as CEPH. The AWS SDK was
also retrying the XML Syntax error request which doesn't make sense.
This change turns off the AWS SDK retries in favour of just using
rclone's retry logic.
Amazon S3 is built to handle different kinds of workloads.
In rare cases where S3 is not able to scale for whatever reason users
will face status 500 errors.
Main mechanism for handling these errors are retries.
Amount of needed retries varies for each different use case.
This change is making retries for s3 backend configurable by using
--low-level-retries option.
Currently each multipart upload allocated his own buffers, which after
file upload was garbaged. Next files couldn't leverage already allocated
memory which resulted in inefficent memory management. This change
introduces backend memory pool keeping memory chunks which can be
used during object operations.
Fixes#3967
The error code 500 Internal Error indicates that Amazon S3 is unable to handle the request at that time. The error code 503 Slow Down typically indicates that the requests to the S3 bucket are very high, exceeding the request rates described in Request Rate and Performance Guidelines.
Because Amazon S3 is a distributed service, a very small percentage of 5xx errors are expected during normal use of the service. All requests that return 5xx errors from Amazon S3 can and should be retried, so we recommend that applications making requests to Amazon S3 have a fault-tolerance mechanism to recover from these errors.
https://aws.amazon.com/premiumsupport/knowledge-center/http-5xx-errors-s3/
The S3 ListObject API returns paginated bucket listings, with
"MaxKeys" items for each GET call.
The default value is 1000 entries, but for buckets with millions of
objects it might make sense to request more elements per request, if
the backend supports it. This commit adds a "list_chunk" option for
the user to specify a lower or higher value.
This commit does not add safe guards around this value - if a user
decides to request a too large list, it might result in connection
timeouts (on the server or client).
In AWS S3, there is a fixed limit of 1000, some other services might
have one too. In Ceph, this can be configured in RadosGW.
Before this patch we were failing to URL decode the NextMarker when
url encoding was used for the listing.
The result of this was duplicated listings entries for directories
with >1000 entries where the NextMarker was a file containing a space.
Before this change we used the same (relatively low limits) for server
side copy as we did for multipart uploads. It doesn't make sense to
use the same limits since no data is being downloaded or uploaded for
a server side copy.
This change introduces a new parameter --s3-copy-cutoff to control
when the switch from single to multipart server size copy happens and
defaults it to the maximum 5GB.
This makes server side copies much more efficient.
It also fixes the erroneous error when trying to set the modification
time of a file bigger than 5GB.
See #3778
Before this change multipart copies were giving the error
Range specified is not valid for source object of size
This was due to an off by one error in the range source introduced in
7b1274e29a "s3: support for multipart copy"
Before this change rclone would allow the user to stream (eg with
rclone mount, rclone rcat or uploading google photos or docs) 5TB
files. This meant that rclone allocated 4 * 525 MB buffers per
transfer which is way too much memory by default.
This change makes rclone use the configured chunk size for streamed
uploads. This is 5MB by default which means that rclone can stream
upload files up to 48GB by default staying below the 10,000 chunks
limit.
This can be increased with --s3-chunk-size if necessary.
If rclone detects that a file is being streamed to s3 it will make a
single NOTICE level log stating the limitation.
This fixes the enormous memory usage.
Fixes#3568
See: https://forum.rclone.org/t/how-much-memory-does-rclone-need/12743
This works around a bug in Ceph which doesn't encode CommonPrefixes
when using URL encoded directory listings.
See: https://tracker.ceph.com/issues/41870
When used with v2_auth = true, PresignRequest doesn't return
signed headers, so remote dest authentication would be fail.
This commit copying back HTTPRequest.Header to headers.
Tested with RiakCS v2.1.0.
Signed-off-by: Anthony Rusdi <33247310+antrusd@users.noreply.github.com>
- Read the storage class for each object
- Implement SetTier/GetTier
- Check the storage class on the **object** before using SetModTime
This updates the fix in 1a2fb52 so that SetModTime works when you are
using objects which have been migrated to GLACIER but you aren't using
GLACIER as a storage class.
Fixes#3522
- change the interface of listBuckets() removing dir parameter and adding context
- add makeBucket() and use in place of Mkdir("")
- this fixes some corner cases in Copy/Update
- mark all the listed buckets OK in ListR
Thanks to @yparitcher for the review.
