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Catena: a transactional, column-oriented storage engine

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#Catena

Overview

Catena is a transactional, column-oriented storage engine. It is designed to be used as part of a larger, data management system. The motivation behind Catena extends to the larger system, so it makes sense to talk a bit about that here.

The vision is to build a complete data management system that is highly conducive to research and experimentation. To accomplish this, we employ 2 simple ideas.

Firstly, provide a clear separation of concerns by defining simple, generalized interfaces among the compiler, optimizer and storage engine compnents. This is so these components can be composed, interchanged and injected dynamically.

Secondly, burn performance analysis into every layer of the system.

Core Concepts

Catena is a column-oriented storage engine, designed to optimize execution of workloads that scan a large number of rows from small number of columns.

Architecture

Catena is composed of a hierarchy of storage abstractions. At the highest level of abstraction are arrays. Arrays are comprised of 1 or more segments.

A segment is in turn comprised of pages, the lowest level abstraction. Pages contain binary data that is read and written to and from segments by arrays.

Pages are completely transient structures that are encapsulated by segments. Each segment corresponds to an on-disk file. The on-disk meta data for a segment consists of the segment's type, page count and size.

Each array resides in its own directory on the local filesystem. Each array directory consists of an array descriptor and 0 or more segments files. The array descriptor file, which is created at the time of array creation, represents the ondisk meta data for the array. It consists of the array type, length and unique identifier. n array is created a descriptor is also created.

Caching

Segments are designed to be loaded into memory as a unit. We call this process pinning a segment. A segment is pinned by pinning each of its pages, and a segment is unpinned by unpinning each of its pages.

To pin a segment we query the cache for its pages. A page query always returns a pinned page. A cache-miss causes the page to be loaded into memory. Both cache-misses and cache-hits increment the pin count and update the statistics.

Segments and Keys

When an array and its descriptor are created, a master key is also created and passed to the descriptor. The master key is a concatenation of the base directory and the array name.

The first segment of an array is associated with a composite key whose first component is the master key and whose second component is 0. As elements are added to the end of the array, eventually, the append-split threshold will be crossed and a new segment will be created. Segments are always created on an even object boundary - an element of an array never spans more than one segment. The new segment will have a composite key that consists of the master key as the first component and the next natural number as the second component.

The array's descriptor also maintains an update-split threshold such that updates to variable length types will never cause the array's size to become unmanageable.

Composite keys are hierarchically collated. When an update-split occurs, Catena creates a new segment between the other segments. To keep track of this an additional component, governed by a natural ordering, is appended. Consider the following keys:

Segment0Key = MasterKey:0
Segment2Key = MasterKey:0:1
Segment1Key = MasterKey:1

The collation defined by the composite key defines the correct ordering for searches.

Registry

A registry manages the meta data of arrays. At startup time, the registry is passed the path to the base directory of the array system, and the registry walks the directory loading the array descriptors and locating their segments.

Deltas are defined as inserts, updates and deletes. Depending on the consistency level, deltas are either automatically committed or are manually committed. When an array is committed all of its deltas and the meta data associated with those are flushed to disk (in the future configuration settings will determine whether commits are flushed to disk or replicated to other nodes in the cluster).

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