while optionally exploiting the exposed information to
orchestrate its data layouts and access patterns.
7 Conclusions
The Atropos disk array LVMemploys a new data organization
that allows applications to take advantage of features
built into modern disks. Striping data in track-sized
units lets them take advantage of zero-latency access to
achieve efficient access for sequential access patterns.
Taking advantage of request scheduling and knowing
exact head switch times enables semi-sequential access,
which results in efficient access to diagonal sets of noncontiguous
By exploiting disk characteristics, a new data organization,
and exposing high-level constructs about this
organization, Atropos can deliver efficient accesses for
database systems, resulting in up to 4 speed-ups for
decision support workloads, without compromising performance
of OLTP workloads.
We thank the members and companies of the PDL
Consortium (including EMC, Hewlett-Packard, Hitachi,
IBM, Intel, LSI Logic, Microsoft, Network Appliance,
Oracle, Panasas, Seagate, Sun, and Veritas) for their
interest, insights, feedback, and support. This work
is funded in part by NSF grants CCR-0113660, IIS-
0133686, and CCR-0205544, and by an IBM faculty
partnership award.
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A Access Efficiency Calculations
Let T(N;K) be the time it takes to service a request of
K sectors that fit onto a single track of a disk with N
sectors per track (i.e., track-aligned access). Ignoring
seek, and assuming no zero-latency access, this time can
be expressed as
Tnzl(N;K) =
N ��1
where the first term is the average rotational latency, and
the second term is the media access time. For disks with
zero-latency access, the first term is not constant; rotational
latency decreases with increasing K. Thus,
Tzl(N;K) =
(N ��K+1)(N+K)
2N2 +
K ��1
These expressions are derived elsewhere [19].
The efficiency of track-based access is the ratio between
the raw one revolution time, Trev, and the time it
takes to read S = kN sectors for some large k. Hence,
En =
k (Ths+Trev)
where Tn(N;N) is the time to read data on the first track,
and (k��1)(Ths+Trev) is the time spent in head switches
and accessing the remaining tracks. In the limit, the access
efficiency is
En(N;H) =1��
which is the maximal streaming efficiency of a disk.
The maximal efficiency of semi-sequential quadrangle
access is simply
Eq(N;H) =
Tzl (N;db+(d��1)H)
with d and b set accordingly.
B Relaxing the one-revolution constraint
Suppose that semi-sequential access to d blocks, each of
size b, from a single quadrangle takes more than one revolution.
Then the inequality in Equation 1 will be larger
than 1. With probability 1=N, a seek will finish with
disk heads positioned exactly at the beginning of the b
sectors mapped to the first track (the upper left corner of
the quadrangle in Figure 12). In this case, the disk will
access all db sectors with maximal efficiency (only incurring
head switch of H sectors for every b-sector read).
However, with probability 1 ��1=N, the disk heads
will land somewhere “in the middle” of the b sectors after
a seek, as illustrated by the arrow in Figure 12. Then,
the access will incur a small rotational latency to access
the beginning of the nearest b sectors, which are, say, on
the k-th track. After this initial rotational latency, which
is, on average, equal to (b��1)=2N, the (d��k)b sectors
mapped onto (d ��k) tracks can be read with maximal
efficiency of the semi-sequential quadrangle access.
b b b b
N-(K mod N)
Collapsing quadrangle with d = 6 into a request of size db+(d-1)H
Physical layout of a quadrangle across disk tracks of size N
head position after seek
Figure 12: An alternative representation of quadrangle access.
To read the remaining k tracks, the disk heads will
need at be positioned to the beginning of the b sectors
on the first track. This will incur a small seek and additional
rotational latency of L=N. Hence, the resulting
efficiency is much lower than when the one-revolution
constraint holds, which avoids this rotational latency.
We can express the total response time for quadrangle
access without the one-revolution constraint as
Tq(N;S) =
where Plat = (N ��H ��b��1)=N is the probability of incurring
the additional rotational latency after reading k
out of d tracks, K = db��(d ��1)H is the effective request
size, L = N ��(K mod N), and S = db is the original
request size. To understand this equation, it may be
helpful to refer to the bottom portion of Figure 12.
The efficiencies of the quadrangle accesses with and
without the one-revolution constraint are approximately
the same when the time spent in rotational latency and
seek for the unconstrained access equals to the time
spent in rotational latency incurred during passing over
dR residual sectors. Hence,
N ��1
N N ��1
Ignoring seek and approximating N ��1 to be N, this occurs
when R 6= 0 and
Thus, in order to achieve the same efficiency for the
non-constrained access, we will have to access at least
d VLBNs. However, this will significantly increase I/O
latency. If R = 0 i.e., when there are no residual sectors,
the one-revolution constraint already yields the most efficient
quadrangle access.

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