Abstract: A large amount of hydrology data are stored in different forms and there are rich varieties of hydrology entity classes. For every type of hydrology entities, some basic description information and series of measuring business data involved in these entities are stored in different way with different update frequency. Hydrology business retrieve requests the index to provide basic descriptive information searching and a kind of combined query based on the relation between basic descriptive information and the business information. However, there is not an efficient index method which can consider several kinds of data and their dependencies. Furthermore, the rapid increasing of hydrology data also brings big challenges to retrieval performance. So, this paper proposes a distributed two-level index HRB based on Hadoop, which creates different index to satisfy different data types and retrieve requirements. The Experiments show that HRB is better at creating index than traditional distributed index, and when the amount of data reaches 10 million levels, HRB index retrieve data is faster. So, HRB has definitive value.

Key words: hydrology entities, two-level index, distributed index, Hadoop