MySQL
Syntax
Jump to
Job options
The following job properties configure the behavior of the ingestion job.
Jump to
MySQL job options:
General job options:
See also:
DDL_FILTERS
DDL_FILTERS
Type: array[string]
Default: ''
(Optional) Comma-separated list of DDL expressions that the job will ignore when there are errors from the Debezium engine.
PARSE_JSON_COLUMNS
PARSE_JSON_COLUMNS
Type: Boolean
Default: false
If enabled, Upsolver will parse JSON columns into a struct matching the JSON value.
SKIP_SNAPSHOTS
— editable
SKIP_SNAPSHOTS
— editableType: Boolean
Default: false
(Optional) By default, snapshots are enabled for new tables. This means that Upsolver will take a full snapshot of the table(s) and ingest it into the staging table before it continues to listen for change events. When set to True
, Upsolver will not take an initial snapshot and only process change events starting from the time the ingestion job is created.
In the majority of cases, when you connect to your source tables, you want to take a full snapshot and ingest it as the baseline of your table. This creates a full copy of the source table in your data lake before you begin to stream the most recent change events. If you skip taking a snapshot, you will not have the historical data in the target table, only the newly added or changed rows.
Skipping a snapshot is useful in scenarios where your primary database instance crashed or became unreachable, failing over to the secondary. In this case, you will need to re-establish the CDC connection but would not want to take a full snapshot because you already have all of the history in your table. In this case, you would want to restart processing from the moment you left off when the connection to the primary database went down.
SNAPSHOT_PARALLELISM
SNAPSHOT_PARALLELISM
Type: int
Default: 1
(Optional) Configures how many snapshots are performed concurrently. The more snapshots performed concurrently, the quicker the tables are streaming. However, doing more snapshots in parallel increases the load on the source database.
Source options
The following data source properties configure how to replicate data from MySQL.
Jump to
TABLE_INCLUDE_LIST
— editable
TABLE_INCLUDE_LIST
— editable
Type: text
Default: ''
(Optional) Comma-separated list of regular expressions that match fully-qualified table identifiers of tables whose changes you want to capture. This maps to the Debezium table.include.list property.
By default, the connector captures changes in every non-system table in all databases. To match the name of a table, Upsolver applies the regular expression that you specify as an anchored regular expression. That is, the specified expression is matched against the entire name string of the table. It does not match substrings that might be present in a table name.
Each RegEx pattern matches against the full string databaseName.tableName
, for example:
RegEx Pattern | Results |
---|---|
db_name.* | Select all tables under |
db_name.users, db_name.items | Selects tables |
db1.items_.* | Selects all tables from |
COLUMN_EXCLUDE_LIST
— editable
COLUMN_EXCLUDE_LIST
— editableType: text
Default: ''
(Optional) Comma-separated list of regular expressions that match the fully-qualified names of columns to exclude from change event record values. This maps to Debezium column.exclude.list property.
By default, the connector matches all columns of the tables listed in TABLE_INCLUDE_LIST
. To match the name of a column, Upsolver applies the regular expression that you specify as an anchored regular expression. That is, the specified expression is matched against the entire name string of the column; it does not match substrings that might be present in a column name.
Each RegEx pattern matches against the full string databaseName.tableName.columnName
, for example:
RegEx Pattern | Results |
---|---|
db.users.address_.* | Selects all of the columns that start with |
db.*.(.*_pii) | Selects all of the columns ending with |
Examples
Ingest multiple tables
The following job creates a synchronized job that replicates the data from the samples.orders and samples.customers tables into the target table in the data lake. Use the TABLE_INCLUDE_LIST
source option to specify which data to ingest.
Disable the initial snapshot
This example uses the SKIP_SNAPSHOTS
option to instruct the job not to take a snapshot. Setting this value to TRUE
ensures that only events that arrive from the time when the job starts, will be ingested. All historical data is ignored.
Exclude columns from ingestion
You can use the TABLE_INCLUDE_LIST
to specify the tables you want to ingest. In the example below, the job will copy data from the customers and orders tables. However, personally identifiable information is stored in these tables, and this data should not be held in the staging or target tables as this would violate privacy laws. The COLUMN_EXCLUDE_LIST
option enables the columns containing sensitive information to be excluded from the ingestion and, in this case, credit_card and customer address data are ignored from the process. This option could equally be used to remove extraneous data.
Last updated