How Hard is Counting Triangles in the Streaming Model

The problem of (approximately) counting the number of triangles in a graph is one of the basic problems in graph theory. In this paper we study the problem in the streaming model. We study the amount of memory required by a randomized algorithm to solve this problem. In case the algorithm is allowed one pass over the stream, we present a best possible lower bound of $Ω(m)$ for graphs $G$ with $m$ edges on $n$ vertices. If a constant number of passes is allowed, we show a lower bound of $Ω(m/T)$, $T$ the number of triangles. We match, in some sense, this lower bound with a 2-pass $O(m/T^{1/3})$-memory algorithm that solves the problem of distinguishing graphs with no triangles from graphs with at least $T$ triangles. We present a new graph parameter $ρ(G)$ -- the triangle density, and conjecture that the space complexity of the triangles problem is $Ω(m/ρ(G))$. We match this by a second algorithm that solves the distinguishing problem using $O(m/ρ(G))$-memory.

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