La integración y el despliegue continuos son prácticas habituales en el desarrollo de software. En el mundo de las bases de datos, esto se traduce en la necesidad de entornos bajo demanda, con estado y efímeros.
El aprovisionamiento de un entorno sin estado no está vinculado a ninguna fuente de datos en particular. Todo lo que se necesita es ejecutar el código que desea probar en su entorno de CI. Esta es la base de la mayoría de las herramientas de CI/CD y no se tratará en este artículo.
La parte un poco más difícil viene de las dependencias que la aplicación necesita para ser probada correctamente, lo que a menudo se conoce como servicios externos. Couchbase es uno de ellos. Hay diferentes maneras de conseguirlos, a través de contenedores Docker por ejemplo, o alojados en tu infraestructura de pruebas, o alguna solución externa como servicio. En realidad no importa, siempre y cuando estén disponibles durante la ejecución de la prueba. Las buenas prácticas serían utilizar variables de entorno para referirse a esas instancias.
Asumiendo que estos servicios se están ejecutando, como una instancia Couchbase Free Tier o un contenedor Docker, el siguiente paso es asegurarse de que están configurados correctamente, y sembrados con los datos necesarios para la prueba.
Hace un tiempo, publiqué un post sobre el uso de Acciones de Couchbase Shell en GitHub. Esto te dirá lo básico sobre el uso de Couchbase Shell con GitHub Actions, pero esto se puede aplicar a la mayoría de las soluciones CI/CD también. Hoy, quiero ir más allá y mostrarte algunos scripts útiles para clonar un clúster o elementos de un clúster para tus entornos bajo demanda.
Uso de Couchbase Shell para clonar entornos
Cuando se usa Couchbase Shell, lo primero que viene a la mente cuando se quiere hacer algo es, ¿hay una función para eso? Por ahora no tenemos una función para clonar algo. La mayoría de las funciones disponibles reflejan las capacidades de nuestras APIs y hoy en día no tenemos APIs de clonación. Pero tenemos la capacidad de escribir scripts, ¡lo que significa que podemos crear los nuestros!
Lo primero que viene a la mente cuando se gestionan bases de datos suele ser recrear la estructura y los esquemas. Como Couchbase es Schemaless, esto sólo consistirá en los buckets, ámbitos, colecciones e índices existentes en el cluster de origen. El primer paso es exportar esa estructura para que pueda ser reimportada más tarde. Esta función listará cada cubo, luego los ámbitos internos y las colecciones, y los añadirá a un array. Después listará todos los índices y los añadirá al JSON de salida.
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# Exports all buckets, scopes, collections and indexes # for the given cluster def export-cluster-struct [ source: string # The cluster to export ] { mut export = [] let buckets = buckets --clusters $source # List the buckets of the given cluster for bucket in $buckets { mut scope_structs = [] let scopes = scopes --clusters $source --bucket $bucket.name for scope in $scopes { let collections = (collections --clusters $source --bucket $bucket.name --scope $scope.scope | reject -i cluster) $scope_structs ++= [{ scope: $scope.scope, collections: $collections }] } # Merge the scopes with the bucket object and add it to the export array let buc = ( $bucket | merge {scopes: $scope_structs } ) $export ++= [ $buc ] } let indexes = query indexes --definitions --disable-context --clusters $source let output = { buckets: $export, indexes: $indexes } return $output } |
Esto funciona porque bajo el capó, Couchbase Shell está usando Nushell, un nuevo tipo de shell que es portable (lo que significa que funciona de la misma manera en Linux, Windows o OS X, lo cual es genial para los scripts CI/CD que tienen que soportar diferentes OS), y que considera cualquier dato de estructura como un DataFrame, haciendo la manipulación de JSON extremadamente fácil.
Para probarlo, ejecute cbshy, a continuación, el archivo que contiene la función. Para mí es ci_scripts.nu. Tengo un cluster ya configurado en mi cbsh config, llamado local
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Laurent Doguin at local in travel-sample.inventory._default > source ci-scripts.nu Laurent Doguin at local in travel-sample.inventory._default > export-cluster-struct local | save local-cluster-export.json |
Ahora bien, si abre local-cluster-export.jsonobtendrá la estructura de su clúster:
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{ "buckets": [ { "cluster": "local", "name": "travel-sample", "type": "couchbase", "replicas": 0, "min_durability_level": "none", "ram_quota": 209715200, "flush_enabled": false, "cloud": false, "max_expiry": 0, "scopes": [ { "scope": "inventory", "collections": [ { "collection": "airport", "max_expiry": "inherited" }, { "collection": "airline", "max_expiry": "inherited" }, { "collection": "route", "max_expiry": "inherited" }, { "collection": "landmark", "max_expiry": "inherited" }, { "collection": "hotel", "max_expiry": "inherited" } ] }, { "scope": "tenant_agent_00", "collections": [ { "collection": "users", "max_expiry": "inherited" }, { "collection": "bookings", "max_expiry": "inherited" } ] }, { "scope": "tenant_agent_01", "collections": [ { "collection": "users", "max_expiry": "inherited" }, { "collection": "bookings", "max_expiry": "inherited" } ] }, { "scope": "tenant_agent_02", "collections": [ { "collection": "users", "max_expiry": "inherited" }, { "collection": "bookings", "max_expiry": "inherited" } ] }, { "scope": "tenant_agent_03", "collections": [ { "collection": "users", "max_expiry": "inherited" }, { "collection": "bookings", "max_expiry": "inherited" } ] }, { "scope": "tenant_agent_04", "collections": [ { "collection": "users", "max_expiry": "inherited" }, { "collection": "bookings", "max_expiry": "inherited" } ] }, { "scope": "_default", "collections": [ { "collection": "_default", "max_expiry": "inherited" } ] }, { "scope": "_system", "collections": [ { "collection": "_query", "max_expiry": "" }, { "collection": "_mobile", "max_expiry": "" } ] } ] } ], "indexes": [ { "bucket": "travel-sample", "scope": "_system", "collection": "_query", "name": "#primary", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE PRIMARY INDEX `#primary` ON `travel-sample`.`_system`.`_query`", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_airportname", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_airportname` ON `travel-sample`(`airportname`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_city", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_city` ON `travel-sample`(`city`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_faa", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_faa` ON `travel-sample`(`faa`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_icao", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_icao` ON `travel-sample`(`icao`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "airline", "name": "def_inventory_airline_primary", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE PRIMARY INDEX `def_inventory_airline_primary` ON `travel-sample`.`inventory`.`airline` WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "airport", "name": "def_inventory_airport_airportname", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_airport_airportname` ON `travel-sample`.`inventory`.`airport`(`airportname`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "airport", "name": "def_inventory_airport_city", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_airport_city` ON `travel-sample`.`inventory`.`airport`(`city`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "airport", "name": "def_inventory_airport_faa", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_airport_faa` ON `travel-sample`.`inventory`.`airport`(`faa`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "airport", "name": "def_inventory_airport_primary", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE PRIMARY INDEX `def_inventory_airport_primary` ON `travel-sample`.`inventory`.`airport` WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "hotel", "name": "def_inventory_hotel_city", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_hotel_city` ON `travel-sample`.`inventory`.`hotel`(`city`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "hotel", "name": "def_inventory_hotel_primary", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE PRIMARY INDEX `def_inventory_hotel_primary` ON `travel-sample`.`inventory`.`hotel` WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "landmark", "name": "def_inventory_landmark_city", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_landmark_city` ON `travel-sample`.`inventory`.`landmark`(`city`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "landmark", "name": "def_inventory_landmark_primary", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE PRIMARY INDEX `def_inventory_landmark_primary` ON `travel-sample`.`inventory`.`landmark` WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "route", "name": "def_inventory_route_primary", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE PRIMARY INDEX `def_inventory_route_primary` ON `travel-sample`.`inventory`.`route` WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "route", "name": "def_inventory_route_route_src_dst_day", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_route_route_src_dst_day` ON `travel-sample`.`inventory`.`route`(`sourceairport`,`destinationairport`,(distinct (array (`v`.`day`) for `v` in `schedule` end))) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "route", "name": "def_inventory_route_schedule_utc", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_route_schedule_utc` ON `travel-sample`.`inventory`.`route`(array (`s`.`utc`) for `s` in `schedule` end) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "inventory", "collection": "route", "name": "def_inventory_route_sourceairport", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_inventory_route_sourceairport` ON `travel-sample`.`inventory`.`route`(`sourceairport`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_name_type", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_name_type` ON `travel-sample`(`name`) WHERE (`_type` = \"User\") WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_primary", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE PRIMARY INDEX `def_primary` ON `travel-sample` WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_route_src_dst_day", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_route_src_dst_day` ON `travel-sample`(`sourceairport`,`destinationairport`,(distinct (array (`v`.`day`) for `v` in `schedule` end))) WHERE (`type` = \"route\") WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_schedule_utc", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_schedule_utc` ON `travel-sample`(array (`s`.`utc`) for `s` in `schedule` end) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_sourceairport", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_sourceairport` ON `travel-sample`(`sourceairport`) WITH { \"defer_build\":true }", "cluster": "local" }, { "bucket": "travel-sample", "scope": "_default", "collection": "_default", "name": "def_type", "status": "Ready", "storage_mode": "memory_optimized", "replicas": 0, "definition": "CREATE INDEX `def_type` ON `travel-sample`(`type`) WITH { \"defer_build\":true }", "cluster": "local" } ] } |
He eliminado ese depósito para realizar esta prueba, con el fin de volver a importarlo más tarde: cubetas caída muestra de viaje.
El siguiente paso lógico es disponer de una función que tome este archivo como entrada y recree la estructura completa en otro clúster:
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# Import all buckets, scopes and collections structure # in the given cluster def import-cluster-struct [ destination: string # The cluster to import ] { let structure = $in # Assigning the piped structure to a variable let buckets = $structure.buckets for bucket in $buckets { $bucket | _create-bucket-definition $destination for scope in ($bucket.scopes | where not ( $it.scope | str starts-with "_" ) ) { print $"Create scope ($destination)_($bucket.name)_($scope.scope)" scopes create --clusters $destination --bucket $bucket.name $scope.scope for col in $scope.collections { print $"Create collection ($destination)_($bucket.name)_($scope.scope)_($col.collection)" collections create --clusters $destination --bucket $bucket.name --scope $scope.scope $col.collection } } } let indexes = $structure.indexes $indexes | _create-indexes $destination # Nushell allows you to use other functions you created } def _create-indexes [ destination: string # the cluster where to create indexes ] { let indexes = $in for index in $indexes { print $"Recreating index ($index.name) on cluster ($destination) with: " print $index.definition query $index.definition --disable-context --clusters $destination } } |
Ahora, para ejecutar esa función:
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Laurent Doguin at local in travel-sample.inventory._default > open local-cluster-export.json | import-cluster-struct capella Laurent Doguin at local in travel-sample.inventory._default > open local-cluster-export.json | import-cluster-struct local Create Bucket local_travel-sample with 200 quota, type couchbase, 0 replicas, none durability, 0 expiry Create scope local_travel-sample_inventory Create collection local_travel-sample_inventory_airport Create collection local_travel-sample_inventory_airline Create collection local_travel-sample_inventory_route Create collection local_travel-sample_inventory_landmark Create collection local_travel-sample_inventory_hotel Create scope local_travel-sample_tenant_agent_00 Create collection local_travel-sample_tenant_agent_00_users Create collection local_travel-sample_tenant_agent_00_bookings Create scope local_travel-sample_tenant_agent_01 Create collection local_travel-sample_tenant_agent_01_users Create collection local_travel-sample_tenant_agent_01_bookings Create scope local_travel-sample_tenant_agent_02 Create collection local_travel-sample_tenant_agent_02_users Create collection local_travel-sample_tenant_agent_02_bookings Create scope local_travel-sample_tenant_agent_03 Create collection local_travel-sample_tenant_agent_03_users Create collection local_travel-sample_tenant_agent_03_bookings Create scope local_travel-sample_tenant_agent_04 Create collection local_travel-sample_tenant_agent_04_users Create collection local_travel-sample_tenant_agent_04_bookings Recreating index #primary on cluster local with: CREATE PRIMARY INDEX `#primary` ON `travel-sample`.`_system`.`_query` Recreating index def_airportname on cluster local with: CREATE INDEX `def_airportname` ON `travel-sample`(`airportname`) WITH { "defer_build":true } Recreating index def_city on cluster local with: CREATE INDEX `def_city` ON `travel-sample`(`city`) WITH { "defer_build":true } Recreating index def_faa on cluster local with: CREATE INDEX `def_faa` ON `travel-sample`(`faa`) WITH { "defer_build":true } Recreating index def_icao on cluster local with: CREATE INDEX `def_icao` ON `travel-sample`(`icao`) WITH { "defer_build":true } Recreating index def_inventory_airline_primary on cluster local with: CREATE PRIMARY INDEX `def_inventory_airline_primary` ON `travel-sample`.`inventory`.`airline` WITH { "defer_build":true } Recreating index def_inventory_airport_airportname on cluster local with: CREATE INDEX `def_inventory_airport_airportname` ON `travel-sample`.`inventory`.`airport`(`airportname`) WITH { "defer_build":true }Recreating index def_inventory_airport_city on cluster local with: CREATE INDEX `def_inventory_airport_city` ON `travel-sample`.`inventory`.`airport`(`city`) WITH { "defer_build":true } Recreating index def_inventory_airport_faa on cluster local with: CREATE INDEX `def_inventory_airport_faa` ON `travel-sample`.`inventory`.`airport`(`faa`) WITH { "defer_build":true } Recreating index def_inventory_airport_primary on cluster local with: CREATE PRIMARY INDEX `def_inventory_airport_primary` ON `travel-sample`.`inventory`.`airport` WITH { "defer_build":true } Recreating index def_inventory_hotel_city on cluster local with: CREATE INDEX `def_inventory_hotel_city` ON `travel-sample`.`inventory`.`hotel`(`city`) WITH { "defer_build":true } Recreating index def_inventory_hotel_primary on cluster local with: CREATE PRIMARY INDEX `def_inventory_hotel_primary` ON `travel-sample`.`inventory`.`hotel` WITH { "defer_build":true } Recreating index def_inventory_landmark_city on cluster local with: CREATE INDEX `def_inventory_landmark_city` ON `travel-sample`.`inventory`.`landmark`(`city`) WITH { "defer_build":true } Recreating index def_inventory_landmark_primary on cluster local with: CREATE PRIMARY INDEX `def_inventory_landmark_primary` ON `travel-sample`.`inventory`.`landmark` WITH { "defer_build":true } Recreating index def_inventory_route_primary on cluster local with: CREATE PRIMARY INDEX `def_inventory_route_primary` ON `travel-sample`.`inventory`.`route` WITH { "defer_build":true } Recreating index def_inventory_route_route_src_dst_day on cluster local with: CREATE INDEX `def_inventory_route_route_src_dst_day` ON `travel-sample`.`inventory`.`route`(`sourceairport`,`destinationairport`,(distinct (array (`v`.`day`) for `v` in `schedule` end))) WITH { "defer_build":true } Recreating index def_inventory_route_schedule_utc on cluster local with: CREATE INDEX `def_inventory_route_schedule_utc` ON `travel-sample`.`inventory`.`route`(array (`s`.`utc`) for `s` in `schedule` end) WITH { "defer_build":true } Recreating index def_inventory_route_sourceairport on cluster local with: CREATE INDEX `def_inventory_route_sourceairport` ON `travel-sample`.`inventory`.`route`(`sourceairport`) WITH { "defer_build":true } Recreating index def_name_type on cluster local with: CREATE INDEX `def_name_type` ON `travel-sample`(`name`) WHERE (`_type` = "User") WITH { "defer_build":true } Recreating index def_primary on cluster local with: CREATE PRIMARY INDEX `def_primary` ON `travel-sample` WITH { "defer_build":true } Recreating index def_route_src_dst_day on cluster local with: CREATE INDEX `def_route_src_dst_day` ON `travel-sample`(`sourceairport`,`destinationairport`,(distinct (array (`v`.`day`) for `v` in `schedule` end))) WHERE (`type` = "route") WITH { "defer_build":true } Recreating index def_schedule_utc on cluster local with: CREATE INDEX `def_schedule_utc` ON `travel-sample`(array (`s`.`utc`) for `s` in `schedule` end) WITH { "defer_build":true } Recreating index def_sourceairport on cluster local with: CREATE INDEX `def_sourceairport` ON `travel-sample`(`sourceairport`) WITH { "defer_build":true } Recreating index def_type on cluster local with: CREATE INDEX `def_type` ON `travel-sample`(`type`) WITH { "defer_build":true } |
Y ahí lo tienes, funciones que te permiten exportar e importar la estructura de datos de un clúster a otro. Aunque este es un buen punto de partida, aún quedan preguntas sobre cómo reimportar datos o sobre la granularidad. Además, es posible que no desees exportar e importar un clúster completo.
Filtrar los buckets que se van a importar es bastante fácil, ya que Nushell permite filtrar marcos de datos:
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Laurent Doguin at local in travel-sample.inventory._default > open local-cluster-export.json | { buckets: ( $in.buckets | where name == 'travel-sample'), indexes :( $in.indexes | where bucket == 'travel-sample') } |
Esto recreará un objeto JSON que solo contiene un bucket llamado viaje-muestra e índices para este bucket.
A partir de ahí, ya debería estar todo listo para gestionar la estructura básica del clúster. ¿Qué pasa con los datos? Hay diferentes formas de importar datos con cbsh, ya que cubre la mayoría de las operaciones clave/valor, así como cualquier consulta INSERT/UPSERT. Y luego tenemos el importación de documentos comando. Su uso es bastante sencillo, solo se necesita una lista de filas con un campo de identificación identificado. Puede ser cualquier cosa que se pueda convertir en un marco de datos para Nushell (XML, CSV, TSV, Parquet y más). Y, por supuesto, puede ser un archivo JSON de una consulta Couchbase SQL++. Este es un ejemplo que guardará el resultado de una consulta en un archivo y lo importará de nuevo a una colección:
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# Save file content to filename let filename = $"temp_($src_bucket)_($src_scope)_($src_collection).json" let query = "SELECT meta().id as meta_id, meta().expiration as expiration, c.* FROM `" + $src_bucket + "`." + $src_scope + "." + $src_collection + " c" query --disable-context --clusters $p.src $query | save -f $filename # Import the file content and print the results print $"Import collection content from ($src)_($src_bucket)_($src_scope)_($src_collection) to ($dest)_($dest_bucket)_($dest_scope)_($dest_collection)" print ( doc import --bucket $p.dest_bucket --scope $p.dest_scope --collection $p.dest_collection --clusters $p.dest --id-column meta_id $filename ) |
Este es un ejemplo concreto, pero el objetivo de utilizar lenguajes de scripting es hacerlos propios. Encontrarás un ejemplo más completo en este GitHub Gist. Es compatible con variables de entorno para el origen y el destino, y puedes decidir si clonar todos los buckets de un clúster, un bucket específico, un ámbito o una colección.
No dude en dejarnos un comentario aquí o en Discordia, siempre estamos buscando sugerencias para mejorar la experiencia global de Couchbase.