Restoring Dictionary Projects

Below are the Dictionary Projects supported on Mainnet. These projects are commonly used, are simple to index and create, but create large datasets.

In order to speed up the onboarding of Indexers, we are providing database snapshots for most of these dictionaries

Downloading Database Snapshots

Network	Deployment ID	Database Size	S3 Bucket URL	SHA256
Polkadot	QmZGAZQ7e1oZgfuK4V29Fa5gveYK3G2zEwvUzTZKNvSBsm	~220GB	S3 URL	c1a1f67e2a205dc9fdd90f738686f3ee57052fcc7bc383a054574ab81e17584f
Kusama	QmXwfCF8858YY924VHgNLsxRQfBLosVbB31mygRLhgJbWn	~260GB	S3 URL	65f6fc3dd0410b296f651369690fd866070dbba8781a61454fc00cc11676452c
Nodle	QmQtmsHoJEYUcxKE4tBqr9Z8kudcgkczQPfhkAxVExQX5y	~15GB	S3 URL	71b52ef798f96c86214213e26a1960477d11f0f80916914159fd2feec2ba17fe
Moonbeam	QmeeqBHdVu7iYnhVE9ZiYEKTWe4jXVUD5pVoGXT6LbCP2t	~123GB	S3 URL	508a47bf84476e222d7ce72d4ca870a41da46d7c2284abdb3db915964d0a69c6
Moonriver	QmXCr6uZFdY1YcGTa4u6ZieQPXK4VHE1Pjy7CBr7ubFwKR	~130GB	S3 URL	db22b7565d8fea385a9e69636eb805079bf6708e898296f27673bc2b4d7a476d
Acala	Qmarrhgrpqw5VK71rMtb4GARpPvq8ajMjAqnjnWZFLV61N	~10G	S3 URL	4f0d8105f45ca856c57fa5f87d102e398e1e99403612c077750cb07bc9839c0d
Karura	QmWumrabg4k6t4EUMhQg19xWwcxGq1hWbcmfmRYiy2Bod5	~10G	S3 URL	046674efb30cdc7ab61b1e834201ac125548e0fafb5f6b69e321a9ddf7b06ae9
Khala	QmYCAns2cunZKJFU85KNK8CvL2ATAmCFVZRdBf963GqWYs	~78G	S3 URL	1b18b40345b7473fb4d8219f1da60381126ec8bbbe064158d2ed5b1b3ad532cd
Westend	Qma6BeSQGHrhP5aydmkQcJCR25TEwuNMogS5boovBBwoeW	~35G	S3 URL	72c94be8187a1298a81a7039900566a80447996899b047f6b4fe3f3066a89bef
Astar	QmUmnKPhcE6JwGMYvY3Yitb5j8qxbQBMxgpkHpVQuXqxDH	~65G	S3 URL	db2c8be67d18e7401290d67b3d7f457dc1881ef0505eb22807487d03b5031e81

You can download the snapshot either from the s3 bucket URL or the BitTorrent magnet link:

Download Snapshot

Downloading via Bittorrent will be faster, you can use your favourite bittorent client or install Aria2

sudo apt update
sudo apt install aria2

aria2c <Magnet_Link>

To download from an S3 bucket

curl -o dictionary.tar <Download_URL>

Restoring the Database Snapshot

This assumes that you have an indexer running locally with admin access to a PostgresQL database (you will be using the pg_restore command).

1. First extract the downloaded snapshot and then extract it using the following command:

tar -xvf dictionary.tar

You will now have a pg dump file called: schema_xxxxxxx.dump

2. Copy the schema_xxxxxxx.dump to .data/postgres/ and then use this command:

docker exec -it indexer_db pg_restore -v -j 2 -h localhost -p 5432 -U postgres -d postgres /var/lib/postgresql/data/schema_xxxxxxx.dump > restore.log 2>&1 &

Note

• please Make sure your indexer_db container is running with healthy status before starting restore process

• We use the -j parameter to update the number of jobs running concurrently. Depending on your machine size, you may want to increase this number to speed up the restore process. Read more

The restore process will start and take quite a long time (like 2 days), please make sure you run this cmd in the background (use tools like tmux/screen/nohup). Here is an example of the output log.

pg_restore: creating SCHEMA "schema_qmzj9whrhrmvn2h"
pg_restore: creating FUNCTION "schema_qmzj9whrhrmvn2h.schema_notification()"
pg_restore: creating TABLE "schema_qmzj9whrhrmvn2h._metadata"
pg_restore: creating TABLE "schema_qmzj9whrhrmvn2h._poi"
pg_restore: creating TABLE "schema_qmzj9whrhrmvn2h.events"
pg_restore: creating TABLE "schema_qmzj9whrhrmvn2h.extrinsics"
pg_restore: creating TABLE "schema_qmzj9whrhrmvn2h.spec_versions"
pg_restore: processing data for table "schema_qmzj9whrhrmvn2h._metadata"
pg_restore: processing data for table "schema_qmzj9whrhrmvn2h._poi"
pg_restore: processing data for table "schema_qmzj9whrhrmvn2h.events"
pg_restore: processing data for table "schema_qmzj9whrhrmvn2h.extrinsics"
pg_restore: processing data for table "schema_qmzj9whrhrmvn2h.spec_versions"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h._metadata _metadata_pkey"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h._poi _poi_chainBlockHash_key"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h._poi _poi_hash_key"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h._poi _poi_mmrRoot_key"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h._poi _poi_parentHash_key"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h._poi _poi_pkey"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h.events events_pkey"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h.extrinsics extrinsics_pkey"
pg_restore: creating CONSTRAINT "schema_qmzj9whrhrmvn2h.spec_versions spec_versions_pkey"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.events_block_height__block_range"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.events_event__block_range"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.events_module__block_range"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.extrinsics_block_height__block_range"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.extrinsics_call__block_range"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.extrinsics_module__block_range"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.extrinsics_tx_hash__block_range"
pg_restore: creating INDEX "schema_qmzj9whrhrmvn2h.poi_hash"
pg_restore: creating TRIGGER "schema_qmzj9whrhrmvn2h._metadata 0xc1aaf8b4176d0f02"

After the data restored, you can start adding the specific project to your service inside admin app, and start indexing the project, the indexing will start basing on the restored data and continue indexing the project.