Mongodb bindata length

Nice, a bunch of useful information, specially the references to MongoDB. Since it seems that we were working we Mongo, we entered the following commands:. When logged in as admin, we could see a form with two fields: If we decode it:. There was also a binary called signer-striped available for download. So it seems we can serialize our payload with pickle, sign it using the signer and submit the payload and the signature.

We have to set up a chroot with qemu-arm64 to emulate the hardware and be able to run the signer. Now, lets go for the payload. This is as far as we got during the game since we didnt have time and decided to go for the Freestyle one.

I decided to post this entry since there are no write-ups in the web and the last part was interesting. In basic MongoDB , the DBWrite lock serializes all access to the oplog, which defines a strict order on write operations as they appear in the oplog, and thus on the order in which they are applied on secondaries.

This ordering is what allows failover elections and rollback to function properly, but the serialization limits write concurrency, which is a fundamental goal for Percona TokuMX. Also in basic MongoDB , the unique identifier for each entry in the oplog is the OpTime, which is a bit timestamp with second resolution and a bit counter that gets reset to 1 each time the timestamp increases. The most significant integer is a sequence number that is incremented each time a new primary is elected.

The least significant integer is a sequence number that is incremented each time an operation commits on the primary. The GTID is stored as a bit BinData value that can be interpreted directly as described above two concatenated bit integers. Consider an oplog entry:. One advantage of the GTID is improved write concurrency. Every write operation in Percona TokuMX constitutes an atomic transaction.

Since these transactions are atomic, each one may constitute a large number of changes, but should either appear fully or not at all in the oplog. For these operations, the GTID plays an important role in write concurrency. Since operations are atomic, they can be large, and committing them to the oplog can be time consuming.

If we required that operations were committed to the oplog sequentially, this would limit write concurrency for some workloads. Instead of making operations serialize with each other when committing and writing to the oplog, TokuMX allows concurrent operations to write to the oplog concurrently, after allocating themselves a new GTID at commit time.

Therefore, the operations may finish writing to the oplog out of GTID-order, but they can do their work concurrently. Rather than ensure that operations write to the oplog in a strict order, we allow operations to commit concurrently, but push this ordering restriction to the secondaries.

Secondaries are not allowed to read operations higher in GTID-order any operation that is not finished committing. The GTID mechanism in Percona TokuMX also provides additional safety in the face of network delays or other forms of clock skew, which are common in large clusters. It can also cause operations that should not be represented in the cluster because they should have been rolled back to be present only on certain machines but not others.

That is, clock skew cannot cause a later operation to appear to come before an earlier operation in the oplog.

In MongoDB , when a write has its Write Concern satisfied for w greater than 1 , this means the write has been replicated to some secondaries, and all subsequent queries on those servers will show the result of the write.

In Percona TokuMX , this is relaxed slightly. So there is a small period of time after a getLastError returns, reporting that replication has completed to w machines, but a query immediately after this might not see the results of the write. However, if the replica set fails over to such a secondary, that machine will guarantee the presence of the write after it is promoted to primary.

In basic MongoDB , the oplog is a capped collection. Starting in Percona TokuMX 1. Periodically, the system creates a new partition and drops the oldest partition. As a result, the command line parameter --oplogSize is deprecated. If the time represented by these settings is less than a day, then a partition is added hourly. Otherwise, a partition is added daily. On upgrade, existing oplogs will be converted to partitioned collections with the old data all in one partition and an empty partition after it for new data.

After expireOplogDays , this large partition will be dropped. If, at the time of upgrade from Percona TokuMX 1. In this case it is a good idea to manually trim the first partition sooner, before space becomes a problem but after the other partitions have accumulated a safe amount of data. Information about the oplog is available in shell commands rs. These provide the same information as the getPartitionInfo for the oplog.

Adding and dropping oplog partitions must be done by the server, to ensure consistency between the oplog. To manually add and drop partitions of the oplog, there are new shell commands rs. Data must exist in the last partition in order to add a partition. To drop partitions, you must use either rs.

Using the example above for rs. Similarly, the time passed to rs. Here are the differences:. Instead, it is an object with two fields, uncompressed and compressed , which show how much user data is in the oplog, and how much space that takes up on disk.

Additionally, there are subdocuments oplog. In Percona TokuMX , it also prints the lag of each secondary behind the primary, in seconds. The purpose of rollback is still the same, to revert write operations on a former primary when the member rejoins a replica set after a failover.

Percona TokuMX , starting in version 2. Each entry in local. This value identifies all entries associated with a single rollback instance. In the example below, they all have value of 0. The GTID of the transaction containing this oplog entry. In the example below, note that the update was part of its own transaction, whereas the other three entries, all inserts, were part of another transaction. In the example below, the first entry, an update, is the only operation done with transaction GTID 1,15 , while the three inserts were done within one transaction, GTID 1, The timestamp of when the rollback algorithm processed that entry.