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3.2.12. Configuring MySQL Cluster Parameters for Local Checkpoints

The parameters discussed in Logging and Checkpointing and in Data Memory, Index Memory, and String Memory that are used to configure local checkpoints for a MySQL Cluster do not exist in isolation, but rather are very much interdepedent on each other. In this section, we illustrate how these parameters — including DataMemory, IndexMemory, NoOfDiskPagesToDiskAfterRestartTUP, NoOfDiskPagesToDiskAfterRestartACC, and NoOfFragmentLogFiles — relate to one another in a working Cluster.

Important

The parameters NoOfDiskPagesToDiskAfterRestartTUP and NoOfDiskPagesToDiskAfterRestartACC were deprecated in MySQL 5.1.6. From MySQL 5.1.6 through 5.1.11, disk writes during LCPs took place at the maximum speed possible. Beginning with MySQL 5.1.12, the speed and throughput for LCPs are controlled using the parameters DiskSyncSize, DiskCheckpointSpeed, and DiskCheckpointSpeedInRestart. See Section 3.2.6, “Defining MySQL Cluster Data Nodes”.

In this example, we assume that our application performs the following numbers of types of operations per hour:

  • 50000 selects

  • 15000 inserts

  • 15000 updates

  • 15000 deletes

We also make the following assumptions about the data used in the application:

  • We are working with a single table having 40 columns.

  • Each column can hold up to 32 bytes of data.

  • A typical UPDATE run by the application affects the values of 5 columns.

  • No NULL values are inserted by the application.

A good starting point is to determine the amount of time that should elapse between local checkpoints (LCPs). It is worth noting that, in the event of a system restart, it takes 40-60 percent of this interval to execute the REDO log — for example, if the time between LCPs is 5 minutes (300 seconds), then it should take 2 to 3 minutes (120 to 180 seconds) for the REDO log to be read.

The maximum amount of data per node can be assumed to be the size of the DataMemory parameter. In this example, we assume that this is 2 GB. The NoOfDiskPagesToDiskAfterRestartTUP parameter represents the amount of data to be checkpointed per unit time — however, this parameter is actually expressed as the number of 8K memory pages to be checkpointed per 100 milliseconds. 2 GB per 300 seconds is approximately 6.8 MB per second, or 700 KB per 100 milliseconds, which works out to roughly 85 pages per 100 milliseconds.

Similarly, we can calculate NoOfDiskPagesToDiskAfterRestartACC in terms of the time for local checkpoints and the amount of memory required for indexes — that is, the IndexMemory. Assuming that we allow 512 MB for indexes, this works out to approximately 20 8-KB pages per 100 milliseconds for this parameter.

Next, we need to determine the number of REDO log files required — that is, fragment log files — the corresponding parameter being NoOfFragmentLogFiles. We need to make sure that there are sufficient REDO log files for keeping records for at least 3 local checkpoints (in MySQL Cluster NDB 6.3.8 and later, we need only allow for 2 local checkpoints). In a production setting, there are always uncertainties — for instance, we cannot be sure that disks always operate at top speed or with maximum throughput. For this reason, it is best to err on the side of caution, so we double our requirement and calculate a number of fragment log files which should be enough to keep records covering 6 local checkpoints (in MySQL Cluster NDB 6.3.8 and later, a number of fragment log files accommodating 4 local checkpoints should be sufficient).

It is also important to remember that the disk also handles writes to the REDO log, so if you find that the amount of data being written to disk as determined by the values of NoOfDiskPagesToDiskAfterRestartACC and NoOfDiskPagesToDiskAfterRestartTUP is approaching the amount of disk bandwidth available, you may wish to increase the time between local checkpoints.

Given 5 minutes (300 seconds) per local checkpoint, this means that we need to support writing log records at maximum speed for 6 * 300 = 1800 seconds (MySQL Cluster NDB 6.3.8 and later: 4 * 300 = 1200 seconds). The size of a REDO log record is 72 bytes plus 4 bytes per updated column value plus the maximum size of the updated column, and there is one REDO log record for each table record updated in a transaction, on each node where the data reside. Using the numbers of operations set out previously in this section, we derive the following:

  • 50000 select operations per hour yields 0 log records (and thus 0 bytes), since SELECT statements are not recorded in the REDO log.

  • 15000 DELETE statements per hour is approximately 5 delete operations per second. (Since we wish to be conservative in our estimate, we round up here and in the following calculations.) No columns are updated by deletes, so these statements consume only 5 operations * 72 bytes per operation = 360 bytes per second.

  • 15000 UPDATE statements per hour is roughly the same as 5 updates per second. Each update uses 72 bytes, plus 4 bytes per column * 5 columns updated, plus 32 bytes per column * 5 columns — this works out to 72 + 20 + 160 = 252 bytes per operation, and multiplying this by 5 operation per second yields 1260 bytes per second.

  • 15000 INSERT statements per hour is equivalent to 5 insert operations per second. Each insert requires REDO log space of 72 bytes, plus 4 bytes per record * 40 columns, plus 32 bytes per column * 40 columns, which is 72 + 160 + 1280 = 1512 bytes per operation. This times 5 operations per second yields 7560 bytes per second.

So the total number of REDO log bytes being written per second is approximately 0 + 360 + 1260 + 7560 = 9180 bytes. Multiplied by 1800 seconds, this yields 16524000 bytes required for REDO logging, or approximately 15.75 MB. The unit used for NoOfFragmentLogFiles represents a set of 4 16-MB log files — that is, 64 MB. Thus, the minimum value (3) for this parameter is sufficient for the scenario envisioned in this example, since 3 times 64 = 192 MB, or about 12 times what is required; the default value of 8 (or 512 MB) is more than ample in this case.