Puede crear un índice de búsqueda vectorial de MongoDB en un Vista para transformar documentos y colecciones de modo que pueda indexar parcialmente una colección, admitir tipos de datos o modelos de datos incompatibles, y más.
Los siguientes ejemplos utilizan el sample_mflix base de datos de muestra.
Nota
Desambiguación
Esta página describe las vistas estándar. Para obtener más información sobre las vistas materializadas bajo demanda, consulte Vistas materializadas bajo demanda.
Para obtener más información sobre las diferencias entre los tipos de vista, consulte Comparación con vistas materializadas a pedido.
Requisitos
Debe utilizar MongoDB 8.0 o superior.
En MongoDB v8.0+:
Utilice la interfaz de usuario de Atlas o la API de administración de Atlas para crear índices de búsqueda vectorial de MongoDB en las vistas.
Ejecute las consultas de búsqueda vectorial de MongoDB en la colección de origen. Haga referencia al índice de búsqueda vectorial de MongoDB creado en la vista. Estas consultas devuelven los documentos originales tal como aparecen en la colección de origen.
En MongoDB v8.1+, también puedes:
Para editar una vista, debe tener un rol de administrador de usuario y utilizar el collMod comando de base de datos.
Limitaciones
MongoDB Vector Search admite vistas con las siguientes etapas:
Los nombres de índice deben ser únicos en una colección de origen y en todas sus vistas.
MongoDB Vector Search no admite definiciones de vistas con operadores que produzcan resultados dinámicos, como la variable de sistema $$USER_ROLES y el operador de agregación $rand.
Las consultas de búsqueda vectorial de MongoDB devuelven los documentos originales tal como aparecen en la colección de origen.
Ejemplo: Filtrar documentos
Para crear una vista, debe tener el privilegio de createCollection.
Puedes filtrar documentos para indexar parcialmente una colección. El siguiente ejemplo crea una vista en la colección sample_mflix.embedded_movies para asegurar que sólo se indexen los documentos que tienen un campo de incrustación de vectores.
➤ Utilice el menú desplegable Seleccione su idioma para configurar la interfaz para los ejemplos de esta página.
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Conéctese al clúster usando mongosh.
Para obtener más información, consulte Conectarse a un clúster a través de mongosh.
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En Atlas, vaya a la Clusters Página para su proyecto.
Si aún no se muestra, seleccione la organización que contiene su proyecto deseado en el menú Organizations de la barra de navegación.
Si aún no aparece, selecciona el proyecto deseado en el menú Projects de la barra de navegación.
En la barra lateral, haz clic en Clusters en la sección Database.
La página de clústeres se muestra.
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En Atlas, vaya a la Search & Vector Search página de su clúster.
Puedes ir a la página de búsqueda de MongoDB desde la opción Search & Vector Search o desde el Data Explorer.
Si aún no aparece, se debe seleccionar la organización que contiene el proyecto en el menú Organizations de la barra de navegación.
Si aún no se muestra, seleccione su proyecto en el menú Projects de la barra de navegación.
En la barra lateral, haz clic en Search & Vector Search en la sección Database.
Si no tienes clústeres, haz clic en Create cluster para crear uno. Para obtener más información, consulta Crear un clúster.
Si el proyecto tiene varios clústeres, se debe seleccionar el clúster que se desea usar en el menú desplegable Select cluster y luego se debe hacer clic en Go to Search.
Aparece la página de Búsqueda y Búsqueda Vectorial.
Si aún no aparece, se debe seleccionar la organización que contiene el proyecto en el menú Organizations de la barra de navegación.
Si aún no se muestra, seleccione su proyecto en el menú Projects de la barra de navegación.
En la barra lateral, haz clic en Data Explorer en la sección Database.
Expanda la base de datos y seleccione la colección.
Haga clic en la pestaña Indexes para la colección.
Haga clic en el enlace Search and Vector Search en el banner.
Aparece la página de Búsqueda y Búsqueda Vectorial.
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Se debe iniciar la configuración del índice.
Realiza las siguientes selecciones en la página y luego haz clic en Next.
Search Type | Seleccione el tipo de índice Atlas Vector Search. |
Index Name and Data Source | Especifique la siguiente información:
|
Configuration Method | For a guided experience, select Visual Editor. To edit the raw index definition, select JSON Editor. |
IMPORTANTE:
El índice de MongoDB Search se llama default por defecto. Si se mantiene este nombre, el índice será el índice de búsqueda por defecto para cualquier query de MongoDB Search que no especifique una opción de index diferente en sus operadores. Si se crean varios índices, recomendamos mantener una convención de nomenclatura coherente y descriptiva en todos los índices.
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Verifique el estado.
El índice recién creado aparece en la pestaña Atlas Search. Mientras se construye el índice, el campo Status muestra Build in Progress. Cuando se termina de construir el índice, el campo Status muestra Active.
Nota
Las colecciones más grandes tardan más en indexarse. Se recibirá una notificación por correo electrónico cuando el índice haya terminado de construirse.
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Ejecuta una query en el índice parcial embeddingsIndex.
Nota
El siguiente ejemplo consulta el índice embeddingsIndex ejecutando el comando .aggregate en la vista moviesWithEmbeddings. Si su clúster ejecuta MongoDB v8.0, debe consultar la colección de origen (por ejemplo, embedded_movies) usando el índice de la vista. Actualice a MongoDB v8.1o superior para consultar la vista directamente.
Guarde las siguientes incrustaciones en un archivo llamado
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Este archivo contiene las incrustaciones para el término de consulta
time travel.En,
mongoshcargue el archivomongoshen para usar las incrustaciones en su consulta:load('/<path-to-file>/query-embeddings.js'); Ejecute la siguiente query:
1 use sample_mflix 2 db.moviesWithEmbeddings.aggregate([ 3 { 4 "$vectorSearch": { 5 "index": "embeddingsIndex", 6 "path": "plot_embedding_voyage_3_large", 7 "queryVector": TIME_TRAVEL_EMBEDDING, 8 "numCandidates": 100, 9 "limit": 10 10 } 11 }, 12 { 13 "$project": { 14 "_id": 0, 15 "plot": 1, 16 "title": 1, 17 } 18 } 19 ]) [ { plot: 'At the age of 21, Tim discovers he can travel in time and change what happens and has happened in his own life. His decision to make his world a better place by getting a girlfriend turns out not to be as easy as you might think.', title: 'About Time' }, { plot: 'A psychiatrist makes multiple trips through time to save a woman that was murdered by her brutal husband.', title: 'Retroactive' }, { plot: 'A time-travel experiment in which a robot probe is sent from the year 2073 to the year 1973 goes terribly wrong thrusting one of the project scientists, a man named Nicholas Sinclair into a...', title: 'A.P.E.X.' }, { plot: 'An officer for a security agency that regulates time travel, must fend for his life against a shady politician who has a tie to his past.', title: 'Timecop' }, { plot: 'After visiting 2015, Marty McFly must repeat his visit to 1955 to prevent disastrous changes to 1985... without interfering with his first trip.', title: 'Back to the Future Part II' }, { plot: 'A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.', title: 'Thrill Seekers' }, { plot: 'Lyle, a motorcycle champion is traveling the Mexican desert, when he find himself in the action radius of a time machine. So he find himself one century back in the past between rapists, ...', title: 'Timerider: The Adventure of Lyle Swann' }, { plot: 'Hoping to alter the events of the past, a 19th century inventor instead travels 800,000 years into the future, where he finds humankind divided into two warring races.', title: 'The Time Machine' }, { plot: 'A romantic drama about a Chicago librarian with a gene that causes him to involuntarily time travel, and the complications it creates for his marriage.', title: "The Time Traveler's Wife" }, { plot: 'A modern aircraft carrier is thrown back in time to 1941 near Hawaii, just hours before the Japanese attack on Pearl Harbor.', title: 'The Final Countdown' } ]
1
Conéctese a su implementación de MongoDB mongosh usando.
Para obtener más información, consulte Conectarse a un clúster a través de mongosh.
3
4
5
Ejecuta una query en el índice parcial embeddingsIndex.
Nota
El siguiente ejemplo consulta el índice embeddingsIndex ejecutando el comando .aggregate en la vista moviesWithEmbeddings. Si su clúster ejecuta MongoDB v8.0, debe consultar la colección de origen (por ejemplo, embedded_movies) usando el índice de la vista. Actualice a MongoDB v8.1o superior para consultar la vista directamente.
Guarde las siguientes incrustaciones en un archivo llamado
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Este archivo contiene las incrustaciones para el término de consulta
time travel.En,
mongoshcargue el archivomongoshen para usar las incrustaciones en su consulta:load('/<path-to-file>/query-embeddings.js'); Ejecute la siguiente query:
1 use sample_mflix 2 db.moviesWithEmbeddings.aggregate([ 3 { 4 "$vectorSearch": { 5 "index": "embeddingsIndex", 6 "path": "plot_embedding_voyage_3_large", 7 "queryVector": TIME_TRAVEL_EMBEDDING, 8 "numCandidates": 100, 9 "limit": 10 10 } 11 }, 12 { 13 "$project": { 14 "_id": 0, 15 "plot": 1, 16 "title": 1, 17 } 18 } 19 ]) [ { plot: 'At the age of 21, Tim discovers he can travel in time and change what happens and has happened in his own life. His decision to make his world a better place by getting a girlfriend turns out not to be as easy as you might think.', title: 'About Time' }, { plot: 'A psychiatrist makes multiple trips through time to save a woman that was murdered by her brutal husband.', title: 'Retroactive' }, { plot: 'A time-travel experiment in which a robot probe is sent from the year 2073 to the year 1973 goes terribly wrong thrusting one of the project scientists, a man named Nicholas Sinclair into a...', title: 'A.P.E.X.' }, { plot: 'An officer for a security agency that regulates time travel, must fend for his life against a shady politician who has a tie to his past.', title: 'Timecop' }, { plot: 'After visiting 2015, Marty McFly must repeat his visit to 1955 to prevent disastrous changes to 1985... without interfering with his first trip.', title: 'Back to the Future Part II' }, { plot: 'A reporter, learning of time travelers visiting 20th century disasters, tries to change the history they know by averting upcoming disasters.', title: 'Thrill Seekers' }, { plot: 'Lyle, a motorcycle champion is traveling the Mexican desert, when he find himself in the action radius of a time machine. So he find himself one century back in the past between rapists, ...', title: 'Timerider: The Adventure of Lyle Swann' }, { plot: 'Hoping to alter the events of the past, a 19th century inventor instead travels 800,000 years into the future, where he finds humankind divided into two warring races.', title: 'The Time Machine' }, { plot: 'A romantic drama about a Chicago librarian with a gene that causes him to involuntarily time travel, and the complications it creates for his marriage.', title: "The Time Traveler's Wife" }, { plot: 'A modern aircraft carrier is thrown back in time to 1941 near Hawaii, just hours before the Japanese attack on Pearl Harbor.', title: 'The Final Countdown' } ]
Consideraciones sobre el rendimiento
Las transformaciones de vista muy complejas pueden causar un rendimiento más lento cuando Atlas lee la vista para filtrar y transformar la colección de origen. En este escenario, se debe considerar crear una vista materializada para evitar una carga adicional de replicación en Atlas. Para evitar la latencia de query causada por la transformación de la vista, se puede consultar la colección de origen directamente para recuperar los documentos originales.
Solucionar problemas
Los índices cambian a FAILED
Los índices cambian al estado FAILED en los siguientes escenarios:
Crea un índice en una vista que es incompatible con MongoDB Vector Search.
Edita una vista de una manera que no cumple con los requisitos de compatibilidad de MongoDB Vector Search.
Elimina o cambia la colección de origen de una vista.
Por ejemplo, si se crea una vista en otra vista y se cambia la fuente de la vista principal a otra colección.
Nota
Esta limitación también se aplica si una vista es descendiente de otras vistas. Por ejemplo, no se puede cambiar ni eliminar la colección de origen de la que provienen todas las descendientes.
Los índices cambian a STALE
Los índices cambian al estado STALE en los siguientes escenarios:
Advertencia
Si la canalización de agregación definida en su vista es incompatible con los documentos de la colección, la replicación de la búsqueda falla. Por ejemplo, si una expresión $toDouble opera en un campo de documento que contiene una matriz, la replicación falla. Asegúrese de que su vista funcione correctamente con todos los documentos de la colección.
Si la definición de la vista provoca un error
READYde agregación mientras un índice es, esteSTALEse convierte en. El índice volverá aREADYdespués de resolver el documento o modificar la definición de la vista para que no vuelva a fallar.STALESi es, el índice sigue siendo consultable. Si el índice se sale del registro de operaciones, se activa su reconstrucción.Si la definición de la vista provoca un error en la canalización de agregación mientras el índice es
BUILDING, la compilación del índice se bloquea hasta que se corrija el documento. El índice volverá aREADYdespués de resolver el documento o modificar la definición de la vista para que no vuelva a fallar.
Puede ver los estados del índice en la interfaz de usuario de Atlas en la página de detalles del estado del índice.
Error: $search solo es válido como primera etapa de una canalización
Este error aparece cuando se consulta una vista utilizando una versión de MongoDB anterior a 8.1.
Si usa una versión de MongoDB anterior a la 8.0, le recomendamos actualizar a la 8.1o superior para consultar la vista directamente. Puede actualizar a la 8.0 para consultar la colección de origen.
Si usa MongoDB 8.0, debe consultar el índice de la vista con la colección de origen. Por ejemplo, ejecute
.aggregate()en la colección en lugar de en la vista.
Proceso de índice
Al crear un índice de búsqueda vectorial de MongoDB en una vista, el proceso mongot realiza las mismas tareas que al crear un índice de búsqueda vectorial de MongoDB en una colección normal. El proceso mongot:
Crea índices de búsqueda vectorial MongoDB basados en las reglas de la definición de índices para la colección.
Supervisa los flujos de cambio para conocer el estado actual de los documentos e índices de las colecciones para las que definió los índices de búsqueda vectorial de MongoDB.
Procesa las consultas de búsqueda vectorial de MongoDB y devuelve los ID de documentos y otros metadatos de búsqueda de los documentos coincidentes a
mongod, que luego realiza una búsqueda completa del documento y devuelve los resultados al cliente.
Cuando se crea un índice de búsqueda vectorial de MongoDB en una vista, la definición de vista se aplica durante el paso 1 y 2, y los documentos transformados se indexan según la definición del índice de búsqueda y luego se almacenan en el disco.
Obtén más información
Para obtener más información sobre las vistas, consulte Vistas.
Para crear un índice de búsqueda de MongoDB en una vista, consulte Usar vistas con búsqueda de MongoDB.