Community

Blog Events Webinars Tutorials Forum
  1. Blog
  2. Events
  3. Webinars
  4. Tutorials
  5. Forum
Create Account
×
Community Blog Migrate DynamoDB to MongoDB Using DynamoShake

Migrate DynamoDB to MongoDB Using DynamoShake

This article introduces the features and architecture of DynamoShake, and describes how to migrate DynamoDB to MongoDB using DynamoShake.

By Zhuzhao

MongoShake and RedisShake are used to migrate, synchronize, and back up data from MongoDB and Redis databases respectively. Recently, the Shake series has expanded further with the launch of DynamoShake (also known as NimoShake), a migration tool for DynamoDB. DynamoShake supports the migration of data from a DynamoDB database to MongoDB. In the future, we will also consider multiple channels, such as direct file backup, migration to Kafka, and migration to other databases like Cassandra and Redis.

GitHub address: https://github.com/alibaba/nimoshake

Basic Features of DynamoShake

DynamoDB supports both full and incremental synchronization. When a process is started, it begins with a full synchronization, followed by incremental synchronization.

The full synchronization consists of two parts: data synchronization and index synchronization. Data synchronization is responsible for synchronizing the data, followed by the synchronization of indexes. Default primary keys are synchronized during the process. However, synchronization of user-created GSIs is only supported in a MongoDB instance within a replica set, and not in Cluster Edition. Incremental synchronization only synchronizes data and does not include generated indexes. It's important to note that during both full and incremental synchronization, DDL operations such as table deletion, table creation, and index creation are not supported.

1

Resumable Upload

Resumable upload is supported in incremental synchronization but not in full synchronization. This means that if an incremental synchronization task is interrupted due to a disconnection and the connection is restored within a short time range, the task can be resumed. However, in certain cases, a full synchronization will be triggered again. For example, if the disconnection lasts for too long or if the previous offset is lost.

Data Synchronization

All source tables will be written into different tables in the destination database (default is dynamo-shake). For example, if you have table1 and table2, after synchronization, you will have a destination database called dynamo-shake that contains table1 and table2. In native DynamoDB, the protocol encloses a layer of type fields in the "key: type: value" format. For instance, if you insert {hello: 1}, the data obtained through the DynamoDB interface will be in the format of {"hello": {"N": 1}}.

All Dynamo data types:

  • String
  • Binary
  • Number
  • StringSet
  • NumberSet
  • BinarySet
  • Map
  • List
  • Boolean
  • Null

Two conversion methods are provided, raw and change. Raw refers to writing the raw data obtained by the DynamoDB interface:

rszz-4.0-2:PRIMARY> use dynamo-shake
switched to db dynamo-shake
rszz-4.0-2:PRIMARY> db.zhuzhao.find()
{ "_id" : ObjectId("5d43f8f8c51d73b1ba2cd845"), "aaa" : { "L" : [ { "S" : "aa1" }, { "N" : "1234" } ] }, "hello_world" : { "S" : "f2" } }
{ "_id" : ObjectId("5d43f8f8c51d73b1ba2cd847"), "aaa" : { "N" : "222" }, "qqq" : { "SS" : [ "h1", "h2" ] }, "hello_world" : { "S" : "yyyyyyyyyyy" }, "test" : { "S" : "aaa" } }
{ "_id" : ObjectId("5d43f8f8c51d73b1ba2cd849"), "aaa" : { "L" : [ { "N" : "0" }, { "N" : "1" }, { "N" : "2" } ] }, "hello_world" : { "S" : " Test Chinese" } }

Change indicates writing data after parsing the type field:

rszz-4.0-2:PRIMARY> use dynamo-shake
switched to db dynamo-shake
rszz-4.0-2:PRIMARY> db.zhuzhao.find()
{ "_id" : ObjectId("5d43f8f8c51d73b1ba2cd845"), "aaa" : [ "aa1", 1234 ] , "hello_world" : "f2" }
{ "_id" : ObjectId("5d43f8f8c51d73b1ba2cd847"), "aaa" : 222, "qqq" : [ "h1", "h2" ] , "hello_world" : "yyyyyyyyyyy", "test" : "aaa" }
{ "_id" : ObjectId("5d43f8f8c51d73b1ba2cd849"), "aaa" : [ 0, 1, 2 ], "hello_world" : "Test Chinese" }

You can specify your synchronization types based on your needs.

Offset

Incremental resumable upload is achieved through the use of offsets. By default, the offset is stored in the destination MongoDB database named dynamo-shake-checkpoint. For each table, a corresponding table is created to record the checkpoint. Additionally, there is a status_table that records whether the current phase is full synchronization or incremental synchronization.

rszz-4.0-2:PRIMARY> use dynamo-shake42-checkpoint
switched to db dynamo-shake42-checkpoint
rszz-4.0-2:PRIMARY> show collections
status_table
zz_incr0
zz_incr1
rszz-4.0-2:PRIMARY>
rszz-4.0-2:PRIMARY>
rszz-4.0-2:PRIMARY> db.status_table.find()
{ "_id" : ObjectId("5d6e0ef77e592206a8c86bfd"), "key" : "status_key", "status_value" : "incr_sync" }
rszz-4.0-2:PRIMARY> db.zz_incr0.find()
{ "_id" : ObjectId("5d6e0ef17e592206a8c8643a"), "shard_id" : "shardId-00000001567391596311-61ca009c", "father_id" : "shardId-00000001567375527511-6a3ba193", "seq_num" : "", "status" : "no need to process", "worker_id" : "unknown-worker", "iterator_type" : "AT_SEQUENCE_NUMBER", "shard_it" : "", "update_date" : "" }
{ "_id" : ObjectId("5d6e0ef17e592206a8c8644c"), "shard_id" : "shardId-00000001567406847810-f5b6578b", "father_id" : "shardId-00000001567391596311-61ca009c", "seq_num" : "", "status" : "no need to process", "worker_id" : "unknown-worker", "iterator_type" : "AT_SEQUENCE_NUMBER", "shard_it" : "", "update_date" : "" }
{ "_id" : ObjectId("5d6e0ef17e592206a8c86456"), "shard_id" : "shardId-00000001567422218995-fe7104bc", "father_id" : "shardId-00000001567406847810-f5b6578b", "seq_num" : "", "status" : "no need to process", "worker_id" : "unknown-worker", "iterator_type" : "AT_SEQUENCE_NUMBER", "shard_it" : "", "update_date" : "" }
{ "_id" : ObjectId("5d6e0ef17e592206a8c86460"), "shard_id" : "shardId-00000001567438304561-d3dc6f28", "father_id" : "shardId-00000001567422218995-fe7104bc", "seq_num" : "", "status" : "no need to process", "worker_id" : "unknown-worker", "iterator_type" : "AT_SEQUENCE_NUMBER", "shard_it" : "", "update_date" : "" }
{ "_id" : ObjectId("5d6e0ef17e592206a8c8646a"), "shard_id" : "shardId-00000001567452243581-ed601f96", "father_id" : "shardId-00000001567438304561-d3dc6f28", "seq_num" : "", "status" : "no need to process", "worker_id" : "unknown-worker", "iterator_type" : "AT_SEQUENCE_NUMBER", "shard_it" : "", "update_date" : "" }
{ "_id" : ObjectId("5d6e0ef17e592206a8c86474"), "shard_id" : "shardId-00000001567466737539-cc721900", "father_id" : "shardId-00000001567452243581-ed601f96", "seq_num" : "", "status" : "no need to process", "worker_id" : "unknown-worker", "iterator_type" : "AT_SEQUENCE_NUMBER", "shard_it" : "", "update_date" : "" }
{ "_id" : ObjectId("5d6e0ef27e592206a8c8647e"), "shard_id" : "shardId-00000001567481807517-935745a3", "father_id" : "shardId-00000001567466737539-cc721900", "seq_num" : "", "status" : "done", "worker_id" : "unknown-worker", "iterator_type" : "LATEST", "shard_it" : "arn:aws:dynamodb:us-east-2:240770237302:table/zz_incr0/stream/2019-08-27T08:23:51.043|1|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", "update_date" : "" }
{ "_id" : ObjectId("5d6e1d807e592206a8c9a102"), "shard_id" : "shardId-00000001567497561747-03819eba", "father_id" : "shardId-00000001567481807517-935745a3", "seq_num" : "39136900000000000325557205", "status" : "in processing", "worker_id" : "unknown", "iterator_type" : "AT_SEQUENCE_NUMBER", "shard_it" : "arn:aws:dynamodb:us-east-2:240770237302:table/zz_incr0/stream/2019-08-27T08:23:51.043|1|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", "update_date" : "" }

The "status_value" : "incr_sync" in the status table indicates that the current phase is incremental synchronization. Each incremental shard records a checkpoint. For more information about shard splitting rules, see DynamoDB Documentation. The following is the description of each field of the incremental table checkpoint:

  • _id: ID of the MongoDB primary key.
  • shard_id: ID of the shard. Each shard has a unique ID.
  • father_id: ID of the parent shard. A shard may have one parent shard.
  • seq_num: Sequence number of the processed shard. This is the primary offset information.

  • status: Current synchronization phase. The following are the states of the process:

    • "not process": Not processed.
    • "no need to process": Unnecessary to process.
    • "prepare stage": Ready to process.
    • "in processing": In processing.
    • "wait father finish": Wait until the parent node is processed.
    • "done": Processed.
  • worker_id: ID of the worker to be processed. This parameter is disabled.
  • iterator_type: Shard traversal mode.
  • shard_it: Iterator address of the shard. This is the secondary offset information.
  • update_date: Timestamp of checkpoint update.

Index

A unique index is created based on the default primary key, and a shard key is created based on the partition key. However, user-created GSI indexes are not created.

Internal Architecture of DynamoShake

This section provides some details about the internal architecture of DynamoShake.

Full Synchronization

The following figure shows the basic architecture of data synchronization for a table. DynamoShake can initiate multiple concurrent TableSyncer threads to pull data, with the concurrency level specified by the user. The fetcher thread retrieves data from the source DynamoDB database and pushes it into queues. Then, the parser thread reads data from the queues and performs parsing, converting Dynamo protocol data into BSON format. Finally, the executor component aggregates and writes the data into the MongoDB database.

2

• Fetcher: Currently, there is only one fetcher thread available, which utilizes the protocol conversion driver provided by AWS. The fetcher feature works by calling the driver to capture data in batches from the source database and placing them into queues until all the source data for the current table is captured. The fetcher thread is separated from the others due to network I/O considerations. Since fetching is affected by network conditions, the process may be relatively slow.

• Parser: Multiple parser threads can be started, with the default value set to 2. The number of parser threads can be specified using the FullDocumentParser parameter. The parser thread reads data from the queues and parses it into the BSON structure. Once the data is parsed, the parser thread writes it as entries to the queues of the executor thread. Since parsing consumes significant CPU resources, the parser thread is separated from the others.

• Executor: Multiple executor threads can be started, with the default value set to 4. The number of executor threads can be specified using the FullDocumentConcurrency parameter. The executor thread pulls data from the queues, aggregates it in batches, and then writes it to the destination MongoDB database. Up to 16 MB of data in 1,024 entries can be aggregated. Once the data from all tables is written, the tableSyncer process will exit.

Incremental Synchronization

The following figure shows the basic architecture of incremental synchronization.

3

The fetcher thread is responsible for detecting changes in shards within the stream. The manager handles message notifications and creates new dispatchers to process messages, with each shard corresponding to one dispatcher. The dispatcher retrieves incremental data from the source, parses and encapsulates it using a batcher, and then writes the data to the MongoDB database through the executor. Simultaneously, the checkpoint is updated. In the case of resumable upload, the dispatcher pulls data from the previous checkpoint instead of starting from the beginning.

Use of DynamoShake

To start, use the command: ./dynamo-shake -conf=dynamo-shake.conf. Configuration parameters are specified in the dynamo-shake.conf file. The following list provides a description of each parameter.

  • id: If you modify the ID, the name of the destination MongoDB database will change.
  • log.file: The path of the log file. If you do not configure this parameter, logs are displayed in standard output.
  • log.level: The log level. The default configuration is recommended.
  • log.buffer: Specifies whether to enable log buffering. The default configuration is recommended.
  • system_profile: Prints the port number of the internal stack. The default configuration is recommended.
  • http_profile: Disabled.
  • sync_mode: The synchronization mode. all indicates full synchronization and incremental synchronization, full indicates full synchronization, and incr indicates incremental synchronization. This parameter is not supported.
  • source.access_key_id: The parameter used to access DynamoDB.
  • source.secret_access_key: The parameter used to access DynamoDB.
  • source.session_token: The parameter used to access DynamoDB. If no temporary key is available, you can skip this parameter.
  • source.region: The parameter used to access DynamoDB.
  • filter.collection.white: The whitelist of names that you want to synchronize. Only data in specified tables is synchronized.
  • filter.collection.black: The blacklist of names that you do not want to synchronize. Data in specified tables is not synchronized.
  • qps.full: The maximum number of requests per second. It is used to limit the frequency of requests during full synchronization.
  • qps.full.batch_num: The maximum number of items included in a request. It is used to limit the number of items during full synchronization.
  • qps.incr: The maximum number of requests per second. It is used to limit the frequency of requests during incremental synchronization.
  • qps.incr.batch_num: The maximum number of items included in a request. It is used to limit the number of items during incremental synchronization.
  • target.type: The configuration of the destination database. Only MongoDB instances are supported.
  • target.address: The connection string of the destination MongoDB instance.
  • target.mongodb.type: The category of the destination MongoDB instance. Valid values: replica and sharding.
  • target.mongodb.exist: Specifies how to handle a second collection with the same name on the destination. The value of drop indicates that the table is deleted, rename indicates that the table is renamed, and empty indicates that the table is not processed.
  • full.concurrency: The number of threads for full synchronization. One thread corresponds to one table.
  • full.document.concurrency: The number of threads for full synchronization used concurrently in a table.
  • full.document.parser: The number of parser threads in a table.
  • full.enable_index.primary: Whether to synchronize the primary key used to access DynamoDB.
  • full.enable_index.user: Whether to synchronize user-created indexes. This parameter is not supported.
  • convert.type: The write mode. The value of raw indicates writing data directly without conversion, and change indicates writing data after parsing the type field. For more information, see the preceding documentation.
  • increase.concurrency: The number of threads for incremental synchronization used concurrently in a table. The maximum number of shards that can be captured at a time.
  • checkpont.address: The storage address of the checkpoint. By default, this parameter is not configured to be the same as that of the destination database.
  • checkpoint.db: The name of the database to which the checkpoint is written. The default value is $db-checkpoint.

DynamoFullCheck

DynamoFullCheck is a tool used to verify the consistency of data between DynamoDB and MongoDB. It currently only supports full data verification and does not support incremental verification. This means that during incremental synchronization, the source and destination databases may be inconsistent.

DynamoFullCheck only supports one-way verification, specifically checking if the data in DynamoDB is a subset of MongoDB. Reverse verification is not performed. Additionally, it supports sampling verification, allowing verification of only the tables of interest.

The verification process consists of the following parts:

  • Brief check. First, it checks if the number of items in the tables on both sides is consistent. Then, it checks if the indexes are consistent (index verification is not supported). If the number of items in the tables is inconsistent, the check terminates.
  • Precise check. The principle of precise check is to pull data from the source and parse it. If there is a unique index, the document is searched in MongoDB according to the unique index, and the consistency is compared. If not, it is searched according to the entire document (heavy workload). Sampling principle:

During precise check, if sampling is enabled, each document is sampled to determine if it needs to be checked. The principle is relatively simple. For example, if the verification is sampled at 30%, a random number is generated from 0 to 100. If it falls within the range of 0 to 30, it will be checked; otherwise, it will not be checked.

When pulling data from the source DynamoDB database, DynamoFullCheck also goes through fetch and parse phases, reusing parts of the DynamoShake code. The difference is that the concurrency of each fetcher, parser, and executor thread in the DynamoFullCheck is 1.

Parameters

The full-check parameter is simpler and is injected directly from the command line. For example, ./dynamo-full-check --sourceAccessKeyID=BUIASOISUJPYS5OP3P5Q --sourceSecretAccessKey=TwWV9reJCrZhHKSYfqtTaFHW0qRPvjXb3m8TYHMe --sourceRegion=ap-east-1 -t="10.1.1.1:30441" --sample=300

Usage:
  dynamo-full-check.darwin [OPTIONS]

Application Options:
  -i, --id=                    target database collection name (default: dynamo-shake)
  -l, --logLevel=
  -s, --sourceAccessKeyID=     dynamodb source access key id
      --sourceSecretAccessKey= dynamodb source secret access key
      --sourceSessionToken=    dynamodb source session token
      --sourceRegion=          dynamodb source region
      --qpsFull=               qps of scan command, default is 10000
      --qpsFullBatchNum=       batch number in each scan command, default is 128
  -t, --targetAddress=         mongodb target address
  -d, --diffOutputFile=        diff output file name (default: dynamo-full-check-diff)
  -p, --parallel=              how many threads used to compare, default is 16 (default: 16)
  -e, --sample=                comparison sample number for each table, 0 means disable (default: 1000)
      --filterCollectionWhite= only compare the given tables, split by ';'
      --filterCollectionBlack= do not compare the given tables, split by ';'
  -c, --convertType=           convert type (default: raw)
  -v, --version                print version

Help Options:
  -h, --help                   Show this help message
MongoDB Database Cloud migration database migration Tutorials DynamoDB DynamoShake
0 1 0
Share on

Read previous post:

ApsaraDB for RDS PostgreSQL Supports PostgreSQL 16.0

Read next post:

Open-Source PolarDB-X 2.3: An Integration of Centralized and Distributed Architectures

ApsaraDB

445 posts | 93 followers

You may also like

Comments

ApsaraDB

445 posts | 93 followers

Related Products

More Posts by ApsaraDB

See All