Data placement is a key factor for high performance database systems. This is particularly true for parallel database systems where data allocation must support both I/O parallelism and processing parallelism within complex queries and between independent queries and transactions. We focus on the allocation of index data and temporary query results that have received little attention so far. In particular, we provide a classification of various approaches for index allocation in parallel DBMS. We then turn to the disk allocation of intermediate query results for which the allocation parameters can be chosen dynamically at query run time. For the case of parallel hash joins, we outline how to determine an optimal approach supporting a high degree of parallelism.