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Add overview section Add data type section Improve function section
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| [[sql-data-types]] | ||
| === Data Type and Mapping | ||
| === Data Types | ||
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| Most of {es} <<mapping-types, data types>> are available in {es-sql}, as indicated below: | ||
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| [cols="^,^,^",options="header"] | ||
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| |=== | ||
| | {es} type | SQL type | SQL precision | ||
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| 3+h| Core types | ||
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| | <<null-value, `null`>> | `null` | 0 | ||
| | <<boolean, `boolean`>> | `boolean` | 1 | ||
| | <<number, `byte`>> | `tinyint` | 3 | ||
| | <<number, `short`>> | `smallint` | 5 | ||
| | <<number, `integer`>> | `integer` | 10 | ||
| | <<number, `long`>> | `long` | 19 | ||
| | <<number, `double`>> | `double` | 15 | ||
| | <<number, `float`>> | `real` | 7 | ||
| | <<number, `half_float`>> | `float` | 16 | ||
| | <<number, `scaled_float`>> | `float` | 19 | ||
| | <<keyword, `keyword`>> | `varchar` | based on <<ignore-above>> | ||
| | <<text, `text`>> | `varchar` | 2,147,483,647 | ||
| | <<binary, `binary`>> | `varbinary` | 2,147,483,647 | ||
| | <<date, `date`>> | `timestamp` | 24 | ||
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| 3+h| Complex types | ||
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| | <<object, `object`>> | `struct` | 0 | ||
| | <<nested, `nested`>> | `struct` | 0 | ||
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| 3+h| Unsupported types | ||
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| | _types not mentioned above_ | `unsupported`| 0 | ||
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| |=== | ||
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| Obviously, not all types in {es} have an equivalent in SQL and vice-versa hence why, {es-sql} | ||
| uses the data type _particularities_ of the former over the latter as ultimately {es} is the backing store. | ||
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| [[sql-multi-field]] | ||
| [float] | ||
| ==== SQL and multi-fields | ||
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| A core concept in {es} is that of an `analyzed` field, that is a full-text value that is interpreted in order | ||
| to be effectively indexed. These fields are of type <<text, `text`>> and are not used for sorting or aggregations as their actual value depends on the <<analyzer, `analyzer`>> used hence why {es} also offers the <<keyword, `keyword`>> type for storing the _exact_ | ||
| value. | ||
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| In most case, and the default actually, is to use both types when for strings which {es} supports through <<multi-fields, multi fields>>, that is the ability to index the same string in multiple ways; for example index it both as `text` for search but also as `keyword` for sorting and aggregations. | ||
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| As SQL requires exact values, when encountering a `text` field {es-sql} will search for an exact multi-field that it can use for comparisons, sorting and aggregations. | ||
| To do that, it will search for the first `keyword` that it can find that is _not_ normalized and use that as the original field _exact_ value. | ||
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| Consider the following `string` mapping: | ||
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| [source, js] | ||
| ---- | ||
| { | ||
| "first_name" : { | ||
| "type" : "text", | ||
| "fields" : { | ||
| "raw" : { | ||
| "type" : "keyword" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| ---- | ||
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| The following SQL query: | ||
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| [source, sql] | ||
| ---- | ||
| SELECT first_name FROM index WHERE first_name = 'John' | ||
| ---- | ||
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| is identical to: | ||
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| [source, sql] | ||
| ---- | ||
| SELECT first_name FROM index WHERE first_name.raw = 'John' | ||
| ---- | ||
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| as {es-sql} automatically _picks_ up the `raw` multi-field from `raw` for exact matching. | ||
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| // TODO finish this | ||
| List of data types in SQL and how they actually map to Elasticsearch. | ||
| Also mention the corner cases - multi-fields, names with dots, etc... |
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| [[sql-overview]] | ||
| == Overview | ||
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| {es-sql} aims to provide a powerful yet lightweight SQL interface to {es}. | ||
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| [[sql-introduction]] | ||
| === Introduction | ||
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| {es-sql} is an X-Pack component that allows SQL-like queries to be executed in real-time against {es}. | ||
| Whether using the REST interface, command-line or JDBC, any client can use SQL to search and aggregate data | ||
| _natively_ inside {es}. | ||
| One can think of {es-sql} as a _translator_, one that understands both SQL and {es} and makes it easy to read and process data in real-time, at scale by leveraging {es} capabilities. | ||
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| [[sql-why]] | ||
| === Why {es-sql} ? | ||
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| Native integration:: | ||
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| {es-sql} is built from the ground up for {es}. Each and every query is efficiently executed against the relevant nodes according to the underlying storage. | ||
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| No external parts:: | ||
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| No need for additional hardware, processes, runtimes or libraries to query {es}; {es-sql} eliminates extra moving parts by running _inside_ the {es} cluster. | ||
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| Lightweight and efficient:: | ||
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| {es-sql} does not abstract {es} and its search capabilities - on the contrary, it embrases and exposes to SQL to allow proper full-text search, in real-time, in the same declarative, succint fashion. | ||
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