  Worst-case optimal join algorithms have so far been studied in two broad
contexts -- $(1)$ when we are given input relation sizes [Atserias et al., FOCS
2008, Ngo et al., PODS 2012, Velduizhen et. al, ICDT 2014] $(2)$ when in
addition to size, we are given a degree bound on the relation [Abo Khamis et
al., PODS 2017]. To the best of our knowledge, this problem has not been
studied beyond these two statistics even for the case when input relations have
arity (at most) two.
  In this paper, we present a worst-case optimal join algorithm when are given
$\ell_{p}$-norm size bounds on input relations of arity at most two for $p \in
(1, 2]$. ($p=1$ corresponds to relation size bounds and $p=\infty$ corresponds
to the degree bounds.) The worst-case optimality holds any fixed $p \in (2,
\infty)$ as well (as long as the join query graph has large enough girth). Our
algorithm is {\em simple}, does not depend on $p$ (or) the $\ell_{p}$-norm
bounds and avoids the (large) poly-log factor associated with the best known
algorithm PANDA [Abo Khamis et al., PODS 2017] for the size and degree bounds
setting of the problem. In this process, we (partially) resolve two open
question from [Ngo, 2018 Gems of PODS]. We believe our algorithm has the {\em
potential} to pave the way for practical worst-case optimal join algorithms
beyond the case of size bounds.
