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<strong id="bit">[Bit](../data-model/#overview):</strong> Bits are the fundamental unit of data in Pilosa. A bit lives in a [frame](#frame), at the intersection of a [row](#row) and [column](#column).
<strong id="bitmap">[Bitmap](../data-model/#overview):</strong> The on-disk and in-memory representation of a [row](#row). Implemented with [Roaring](#roaring-bitmap).
<strong id="bitmap">[Bitmap](../data-model/#overview):</strong> The on-disk and in-memory representation of a [row](#row). Implemented with [Roaring](#roaring-bitmap). `Bitmap` is also the basic [PQL](#pql) query for reading a Bitmap.
<strong id="bsi">[BSI](../data-model/#bsi-range-encoding)</strong> Bit-sliced indexing is the method Pilosa uses to represent multi-bit integers. Integer values are stored in [fields](#field), and can be used for [Range](#range) and [Sum](#sum) queries.
<strong id="cluster">Cluster:</strong> A cluster consists of one or more [nodes](#node) which share a cluster configuration. The cluster also defines how data is [replicated](#replica) throughout and how internode communication is coordinated. Pilosa does not have a leader node, all data is evenly distributed, and any node can respond to queries.
<strong id="column">[Column](../data-model/#column):</strong> Columns are the fundamental horizontal data axis within Pilosa. Columns are global to all [frames](#frame) within an [index](#index).
<strong id="field">[Field](../data-model/#bsi-range-encoding):</strong> A group of rows used to store integer values with [BSI](#bsi), for use in [Range](#range) and [Sum](#sum) queries.
<strong id="fragment">Fragment:</strong> A Fragment is the intersection of a [frame](#frame) and a [slice](#slice) in an [index](#index).
<strong id="frame">[Frame](../data-model/#frame):</strong> Frames are used to group [rows](#row) into different categories. `RowID`s are namespaced by frame such that the same `RowID` in a different frame refers to a different row. For [ranked](#topn) frames, rows are kept in sorted order within the frame.
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<strong id="node">Node:</strong> An individual running instance of Pilosa server which belongs to a [cluster](#cluster).
<strong id="partition">Partition:</strong> The [consistent hash](#jump-consistent-hash) maps keys to partitions (or locations on the unit circle), based on a preset maximum number of partitions (256 by default). Partitions are then evenly mapped to physical [nodes](#node). To add nodes to the [cluster](#cluster), the partitions must be remapped, and data is then associated across the new cluster topology.
<strong id="partition">Partition:</strong> The [consistent hash](#jump-consistent-hash) maps keys to partitions (or locations on the unit circle), based on a preset maximum number of partitions. Partitions are then evenly mapped to physical [nodes](#node). To add nodes to the [cluster](#cluster), the partitions must be remapped, and data is then associated across the new cluster topology. `DefaultPartitionN` is 256. It can be modified, but only at compile time, and before ingesting any data.
<strong id="pql">[PQL](../query-language/):</strong> Pilosa Query Language.
<strong id="protobuf">[Protobuf](https://developers.google.com/protocol-buffers/):</strong> Protocol Buffers is a binary serialization format which Pilosa uses for internal messages, and can be used by clients as an alternative to JSON.
<strong id="range">[Range](../query-lanuage/#range):</strong>: A [PQL](#pql) query that returns bits based on comparison to timestamps, set according to the [time quantum](#time-quantum).
<strong id="range">[Range (BSI)](../query-lanuage/#range-bsi):</strong>: A [PQL](#pql) query that returns bits based on comparison to integers stored in [BSI](#bsi) [fields](#field).
<strong id="replica">[Replica](../configuration/#cluster-replicas):</strong> A copy of a [fragment](#fragment) on a different [node](#node) than the original. The `cluster.replicas` configuration parameter determines how many replicas of a fragment exist in the cluster. This includes the original, so a value of 1 means no extra copies are made.
<strong id="roaring-bitmap">[Roaring Bitmap](http://roaringbitmap.org):</strong> the compressed bitmap format which Pilosa uses to [implement bitmaps](../architecture/#roaring-bitmap-storage-format), for both storage and logical query operations.
<strong id="row">[Row](../data-model/#row):</strong> Rows are the fundamental vertical data axis within Pilosa. They are namespaced to each [frame](#frame) within an [index](#index). Represented as a [bitmap][#bitmap].
<strong id="row">[Row](../data-model/#row):</strong> Rows are the fundamental vertical data axis within Pilosa. They are namespaced to each [frame](#frame) within an [index](#index). Represented as a [Bitmap](#bitmap).
<strong id="slice">[Slice](../data-model/#slice):</strong> [Columns](#column) are sharded on a preset [width](#slicewidth). Each shard is referred to as a slice in Pilosa. Slices are operated on in parallel and are evenly distributed across the cluster via a [consistent hash](#jump-consistent-hash).
<strong id="slicewidth">SliceWidth:</strong> This is the number of [columns](#column) in a [slice](#slice). By default, 2<sup>20</sup> or about one million.
<strong id="slicewidth">SliceWidth:</strong> This is the number of [columns](#column) in a [slice](#slice). `SliceWidth` defaults to 2<sup>20</sup> or about one million. It can be modified, but only at compile time, and before ingesting any data.
<strong id="tanimoto">[Tanimoto](../examples/#chemical-similarity-search):</strong> Used for similarity queries on Pilosa data. The [Tanimoto Coefficient](https://en.wikipedia.org/wiki/Jaccard_index#Tanimoto_similarity_and_distance) between two [bitmaps](#bitmap) A and B is the ratio of the size of their intersection to the size of their union (|A∩B|/|A∪B|).
<strong id="sum">[Sum](../query-language/#sum):</strong> A [PQL](#pql) query that returns the sum of integers stored in [BSI](#bsi) [fields](#field).
<strong id="tanimoto">[Tanimoto](../examples/#chemical-similarity-search):</strong> Used for similarity queries on Pilosa data. The [Tanimoto Coefficient](https://en.wikipedia.org/wiki/Jaccard_index#Tanimoto_similarity_and_distance) between two [Bitmaps](#bitmap) A and B is the ratio of the size of their intersection to the size of their union (|A∩B|/|A∪B|).
<strong id="time-quantum">[Time quantum](../data-model/#time-quantum):</strong> Defines the granularity to be used for time [Range](#range) queries.
<strong id="toml">[TOML](https://github.com/toml-lang/toml):</strong> the language used for Pilosa's [configuration file](../configuration).
<strong id="topn">TopN:</strong> A [PQL](#pql) query that returns a list of `RowID`s, sorted by the count of [bits](#bit) set in the [row](#row), within a specified [frame](#frame).
<strong id="topn">[TopN](../query-language#topn):</strong> A [PQL](#pql) query that returns a list of `RowID`s, sorted by the count of [bits](#bit) set in the [row](#row), within a specified [frame](#frame).
<strong id="view">[View](../data-model/#view):</strong> Views separate the different data layouts within a [Frame](#frame). The two primary views are standard and inverse which represent the typical [row](#row)/[column](#column) data and its inverse respectively (an [inverted index](https://en.wikipedia.org/wiki/Inverted_index), or a matrix transpose). Time based frame views are automatically generated for each time quantum. Views are internally managed by Pilosa, and never exposed directly via the API. This simplifies the functional interface by separating it from the physical data representation.
<strong id="view">[View](../data-model/#view):</strong> Views separate the different data layouts within a [Frame](#frame). The two primary views are standard and inverse which represent the typical [row](#row)/[column](#column) data and its inverse respectively (an [inverted index](https://en.wikipedia.org/wiki/Inverted_index), or a matrix transpose). Time based frame views are automatically generated for each [time quantum](#time-quantum). Views are internally managed by Pilosa, and never exposed directly via the API. This simplifies the functional interface by separating it from the physical data representation.