Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Menulis data ke database Firestore
Halaman ini menjelaskan tahap kedua dari
proses migrasi saat
Anda menyiapkan pipeline Dataflow dan memulai pemindahan data serentak
dari bucket Cloud Storage ke database Firestore dengan kompatibilitas MongoDB
tujuan Anda. Operasi ini
akan berjalan secara bersamaan dengan aliran Datastream.
Mulai pipeline Dataflow
Perintah berikut memulai pipeline Dataflow baru dengan nama unik.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[],[],null,["# Write data to the Firestore database\n====================================\n\nThis page describes the second stage of the\n[migration process](/firestore/mongodb-compatibility/docs/migrate-data) where\nyou set up a Dataflow pipeline and begin a concurrent data move\nfrom the Cloud Storage bucket into your destination\nFirestore with MongoDB compatibility database. This operation\nwill run concurrently with the Datastream stream.\n\nStart the Dataflow pipeline\n---------------------------\n\nThe following command starts a new, uniquely named, Dataflow\npipeline.\n**Note:** The start timestamp of the job is captured in the `DATAFLOW_START_TIME` environment variable. Make a note of this timestamp: it will appear as part of the job name in the Dataflow console. \n\n DATAFLOW_START_TIME=\"$(date +'%Y%m%d%H%M%S')\"\n\n gcloud dataflow flex-template run \"dataflow-mongodb-to-firestore-$DATAFLOW_START_TIME\" \\\n --template-file-gcs-location gs://dataflow-templates-us-central1/latest/flex/Cloud_Datastream_MongoDB_to_Firestore \\\n --region $LOCATION \\\n --num-workers $NUM_WORKERS \\\n --temp-location $TEMP_OUTPUT_LOCATION \\\n --additional-user-labels \"\" \\\n --parameters inputFilePattern=$INPUT_FILE_LOCATION,\\\n inputFileFormat=avro,\\\n fileReadConcurrency=10,\\\n connectionUri=$FIRESTORE_CONNECTION_URI,\\\n databaseName=$FIRESTORE_DATABASE_NAME,\\\n shadowCollectionPrefix=shadow_,\\\n batchSize=500,\\\n deadLetterQueueDirectory=$DLQ_LOCATION,\\\n dlqRetryMinutes=10,\\\n dlqMaxRetryCount=500,\\\n processBackfillFirst=false,\\\n useShadowTablesForBackfill=true,\\\n runMode=regular,\\\n directoryWatchDurationInMinutes=20,\\\n streamName=$DATASTREAM_NAME,\\\n stagingLocation=$STAGING_LOCATION,\\\n autoscalingAlgorithm=THROUGHPUT_BASED,\\\n maxNumWorkers=$MAX_WORKERS,\\\n workerMachineType=$WORKER_TYPE\n\nFor more information about monitoring the Dataflow pipeline,\nsee\n[Troubleshooting](/firestore/mongodb-compatibility/docs/migrate-troubleshooting).\n\nWhat's next\n-----------\n\nProceed to\n[Migrate traffic to Firestore](/firestore/mongodb-compatibility/docs/migrate-traffic)."]]
