Typical CarbonData Performance Tuning Parameters

This section describes the configurations that can improve CarbonData performance.

Table 1 and Table 2 describe the configurations about query of CarbonData.

**Table 1** Number of tasks started for the shuffle process
Parameter	spark.sql.shuffle.partitions
Configuration File	spark-defaults.conf
Function	Data query
Scenario Description	Number of tasks started for the shuffle process in Spark
Tuning	You are advised to set this parameter to one to two times as much as the executor cores. In an aggregation scenario, reducing the number from 200 to 32 can reduce the query time by two folds.

**Table 2** Number of executors and vCPUs, and memory size used for CarbonData data query
Parameter	spark.executor.cores spark.executor.instances spark.executor.memory
Configuration File	spark-defaults.conf
Function	Data query
Scenario Description	Number of executors and vCPUs, and memory size used for CarbonData data query
Tuning	In the bank scenario, configuring 4 vCPUs and 15 GB memory for each executor will achieve good performance. The two values do not mean the more the better. Configure the two values properly in case of limited resources. If each node has 32 vCPUs and 64 GB memory in the bank scenario, the memory is not sufficient. If each executor has 4 vCPUs and 12 GB memory, Garbage Collection may occur during query, time spent on query from increases from 3s to more than 15s. In this case, you need to increase the memory or reduce the number of vCPUs.

Table 3, Table 4, and Table 5 describe the configurations for CarbonData data loading.

**Table 3** Number of vCPUs used for data loading
Parameter	carbon.number.of.cores.while.loading
Configuration File	carbon.properties
Function	Data loading
Scenario Description	Number of vCPUs used for data processing during data loading in CarbonData
Tuning	If there are sufficient CPUs, you can increase the number of vCPUs to improve performance. For example, if the value of this parameter is changed from 2 to 4, the CSV reading performance can be doubled.

**Table 4** Whether to use Yarn local directories for multi-disk data loading
Parameter	carbon.use.local.dir
Configuration File	carbon.properties
Function	Data loading
Scenario Description	Whether to use Yarn local directories for multi-disk data loading
Tuning	If this parameter is set to true, CarbonData uses local Yarn directories for multi-table load disk load balance, improving data loading performance.

**Table 5** Whether to use multiple directories during loading
Parameter	carbon.use.multiple.temp.dir
Configuration File	carbon.properties
Function	Data loading
Scenario Description	Whether to use multiple temporary directories to store temporary sort files
Tuning	If this parameter is set to true, multiple temporary directories are used to store temporary sort files during data loading. This configuration improves data loading performance and prevents single points of failure (SPOFs) on disks.

Table 6 describes the configurations for CarbonData data loading and query.

**Table 6** Number of vCPUs used for data loading and query
Parameter	carbon.compaction.level.threshold
Configuration File	carbon.properties
Function	Data loading and query
Scenario Description	For minor compaction, specifies the number of segments to be merged in stage 1 and number of compacted segments to be merged in stage 2.
Tuning	Each CarbonData load will create one segment, if every load is small in size, it will generate many small files over a period of time impacting the query performance. Configuring this parameter will merge the small segments to one big segment which will sort the data and improve the performance. The compaction policy depends on the actual data size and available resources. For example, a bank loads data once a day and at night when no query is performed. If resources are sufficient, the compaction policy can be 6 or 5.

**Table 7** Whether to enable data pre-loading when the index cache server is used
Parameter	carbon.indexserver.enable.prepriming
Configuration File	carbon.properties
Function	Data loading
Scenario Description	Enabling data pre-loading during the use of the index cache server can improve the performance of the first query.
Tuning	You can set this parameter to true to enable the pre-loading function. The default value is false.