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The first three group tests are based on the last release version which can be use as baseline for comparing the following test results. The last 6*3=18 rows correspond to the 6 types of query test based on latest master branch. After ingestion test, three groups of query tests will be conducted. The first group gets the none-cache query performance results while the second and third groups get cached. Since query test is after ingestion query, the query result can be easily mapped to IoTDB version by looking at projectID. queryResult.csv introduction (except obvious fields): Field: Description projectID: Unique test instance mark. avg: Average time cost of all query operations. [ms] midAvg: Average time cost of query operations without 5% head and tail. [ms] min: Min time cost of all query operations. [ms] max: Max time cost of all query operations. [ms] p1: 1 percentile of all query operations time cost. [ms] totalTimes: Max accumulative query operation time cost of the clients. [s] totalPoints: Number of total query result points. queryNumber: Number of query operation. Eight Query Types: 1. aggTi: Aggregation Query with Time Filter query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 aggregation function: max_value time filter range: 250000 ms 500 query operations example: SELECT max_value(s_72) FROM root.perform.group_0.d_68 WHERE time >= 2018-08-30 02:55:50 AND time <= 2018-08-30 03:00:00 2. aggVa: Aggregation Query with Value Filter query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 aggregation function: max_value time filter range: 250000 ms 500 query operations example: SELECT max_value(s_25) FROM root.perform.group_1.d_102 WHERE root.perform.group_1.d_102.s_25 > 1.0 3. criteri: Criteria Query (Simple Query with Time and Value Filter) query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 time filter range: 250000 ms value filter: > 1 500 query operations example: SELECT s_35 FROM root.perform.group_4.d_462 WHERE time >= 2018-08-30 03:10:00 AND time <= 2018-08-30 03:14:10 AND root.perform.group_4.d_462.s_35 > 1.0 4. exact: Exact Query query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 500 query operations example: SELECT s_75 FROM root.perform.group_7.d_731 WHERE time = 2018-08-30 02:25:00 5. group: Group-By Query query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 time filter range: 250000 ms time unit: 20000 ms aggregation function: max_value 500 query operations example: SELECT max_value(s_38) FROM root.perform.group_11.d_1171 GROUP BY(20000ms, 1535558400000,[2018-08-30 03:07:30,2018-08-30 03:11:40]) 6. latest: MAX_TIME Query query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 aggregation function: max_time 500 query operations example: SELECT max_time(s_0) FROM root.performf.group_0.d_2 7. limit: limit Query query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 time filter range: 250000 ms 500 query operations example: SELECT * FROM root.perform.group_0.d_0 limit 5 offset 5 slimit 5 soffset 5 8. range: Range Query query workload: number of involved sensor in each query: 1 number of involved device in each query: 1 time filter range: 250000 ms 500 query operations example: SELECT s_0 FROM root.performf.group_0.d_2 WHERE time >= 2010-01-01 12:00:00 AND time <= 2010-01-01 12:04:10 Configurations: Data set is generated by ingestion test: 20 storage groups 2000 devices in total 100 sensors per device 50% out-of-order data Hardware: 32G memory 8 threads CPU 1000Mbit ethernet IoTDB: MAX_HEAP_SIZE="20G" meta_data_cache_enable=true(as default) filemeta_chunkmeta_free_memory_proportion=3:6:10(as default) The rest parameters are default.
