Users new to ClickHouse often struggle to fully understand its primary key concepts. Unlike B(+)-Tree-based OLTP databases, which are optimized for fast location of specific rows, ClickHouse utilizes a sparse index designed for millions of inserted rows per second and petabyte-scale datasets. In contrast to OLTP databases, this index relies on the data on disk being sorted for fast identification of groups of rows that could possibly match a query - a common requirement in analytical queries. The index, in effect, allows the matching sections of part files to be rapidly identified before they are streamed into the processing engine. For more detail on the layout of the data on disk, we highly recommend this guide.
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Observed Behavior。关于这个话题，新收录的资料提供了深入分析
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从我们入库企业的数量看，亿元和千万元级别是企业分布数量最多的两个区间，5029 家企业，占比超过八成（85.02%），研发投入合计7734.02 亿元，占比接近三成（28.50%）。