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Description
During query performance testing, it was found that querying all data rows for a key incurs the least time cost; querying a subset of data within a specified time range for a key results in a relatively increased time cost; querying data for a specific timestamp for a key results in an even greater increase in time cost.
Detail:
table:import TalkingData train dataset (180+ million rows) into openmldb
query key: ip=88
Description
During query performance testing, it was found that querying all data rows for a key incurs the least time cost; querying a subset of data within a specified time range for a key results in a relatively increased time cost; querying data for a specific timestamp for a key results in an even greater increase in time cost.
Detail:
table:import TalkingData train dataset (180+ million rows) into openmldb
query key: ip=88
more result detail: https://qiok3h8ob4.feishu.cn/docx/YkYfdBZm9oVk0MxLFx9co8lLn1g?from=from_copylink
Expected Behavior
querying smaller amounts of data should have shorter time costs, or at least not longer than querying larger amounts of data.
Steps to Reproduce
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