Chapter 4. Configuration

Table of Contents

4.1. Node Properties
4.2. Node
4.3. Node Group
4.4. Node Group Link
4.5. Channel
4.6. Triggers, Routers, and Trigger / Routers Mappings
4.6.1. Trigger
4.6.1.1. Large Objects
4.6.1.2. External Select
4.6.2. Router
4.6.2.1. Default Router
4.6.2.2. Column Match Router
4.6.2.3. Lookup Table Router
4.6.2.4. Subselect Router
4.6.2.5. Scripted Router
4.6.2.6. Audit Table Router
4.6.2.7. Utilizing External Select when Routing
4.6.3. Trigger / Router Mappings
4.6.3.1. Enable / disable trigger router
4.6.3.2. Initial Loads
4.6.3.3. Dead Triggers
4.6.3.4. Enabling "Ping Back"
4.7. Opening Registration
4.8. Transforming Data
4.8.1. Transform Configuration Tables
4.8.2. Transformation Types
4.9. Data Load Filters
4.9.1. Load Filter Configuration Table
4.9.2. Variables available to Data Load Filters
4.9.3. Data Load Filter Example
4.10. Conflict Detection and Resolution
4.11. File Synchronization
4.11.1. Overview
4.11.2. Operation
4.11.3. File Sync Bean Shell Scripts
4.11.4. File Sync Examples
4.11.4.1. Sync Text Files From Server To Client
4.11.4.2. Route changes to a specific node based on a directory name
4.12. Jobs
4.12.1. Route Job
4.12.1.1. Data Gaps
4.12.2. Push and Pull Jobs for Database changes
4.12.3. File Sync Push and Pull Jobs
4.12.4. File System Tracker Job
4.12.5. Sync Triggers Job
4.12.6. Purge Jobs

Chapter 3 introduced numerous concepts and the analysis and design needed to create an implementation of SymmetricDS. This chapter re-visits each analysis step and documents how to turn a SymmetricDS design into reality through configuration of the various SymmetricDS tables. In addition, several advanced configuration options, not presented previously, will also be covered.

4.1. Node Properties

To get a SymmetricDS node running, it needs to be given an identity and it needs to know how to connect to the database it will be synchronizing. The preferred way to configure a SymmetricDS engine is to create a properties file in the engines directory. The SymmetricDS server will create an engine for each properties file found in the engines directory. When started up, SymmetricDS reads the synchronization configuration and state from the database. If the configuration tables are missing, they are created automatically (auto creation can be disabled). Basic configuration is described by inserting into the following tables (the complete data model is defined in Appendix A, Data Model ).

  • NODE_GROUP - specifies the tiers that exist in a SymmetricDS network

  • NODE_GROUP_LINK - links two node groups together for synchronization

  • CHANNEL - grouping and priority of synchronizations

  • TRIGGER - specifies tables, channels, and conditions for which changes in the database should be captured

  • ROUTER - specifies the routers defined for synchronization, along with other routing details

  • TRIGGER_ROUTER - provides mappings of routers and triggers

During start up, triggers are verified against the database, and database triggers are installed on tables that require data changes to be captured. The Route, Pull and Push Jobs begin running to synchronize changes with other nodes.

Each node requires properties that allow it to connect to a database and register with a parent node. Properties are configured in a file named xxxxx.properties that is placed in the engines directory of the SymmetricDS install. The file is usually named according to the engine.name, but it is not a requirement.

To give a node its identity, the following properties are required. Any other properties found in conf/symmetric.properties can be overridden for a specific engine in an engine's properties file. If the properties are changed in conf/symmetric.properties they will take effect across all engines deployed to the server. Note that you can use the variable $(hostName) to represent the host name of the machine when defining these properties (for example, external.id=$(hostName) ).

engine.name

This is an arbitrary name that is used to access a specific engine using an HTTP URL. Each node configured in the engines directory must have a unique engine name. The engine name is also used for the domain name of registered JMX beans.

group.id

The node group that this node is a member of. Synchronization is specified between node groups, which means you only need to specify it once for multiple nodes in the same group.

external.id

The external id for this node has meaning to the user and provides integration into the system where it is deployed. For example, it might be a retail store number or a region number. The external id can be used in expressions for conditional and subset data synchronization. Behind the scenes, each node has a unique sequence number for tracking synchronization events. That makes it possible to assign the same external id to multiple nodes, if desired.

sync.url

The URL where this node can be contacted for synchronization. At startup and during each heartbeat, the node updates its entry in the database with this URL. The sync url is of the format: http://{hostname}:{port}/{webcontext}/sync/{engine.name} .

The {webcontext} is blank for a standalone deployment. It will typically be the name of the war file for an application server deployment.

The {engine.name} can be left blank if there is only one engine deployed in a SymmetricDS server.

When a new node is first started, it is has no information about synchronizing. It contacts the registration server in order to join the network and receive its configuration. The configuration for all nodes is stored on the registration server, and the URL must be specified in the following property:

registration.url

The URL where this node can connect for registration to receive its configuration. The registration server is part of SymmetricDS and is enabled as part of the deployment. This is typically equal to the value of the sync.url of the registration server.

Important

Note that a registration server node is defined as one whose registration.url is either (a) blank, or (b) identical to its sync.url .

For a deployment where the database connection pool should be created using a JDBC driver, set the following properties:

db.driver

The class name of the JDBC driver.

db.url

The JDBC URL used to connect to the database.

db.user

The database username, which is used to login, create, and update SymmetricDS tables.

db.password

The password for the database user.

4.2. Node

A node , a single instance of SymmetricDS, is defined in the NODE table. Two other tables play a direct role in defining a node, as well The first is NODE_IDENTITY . The only row in this table is inserted in the database when the node first registers with a parent node. In the case of a root node, the row is entered by the user. The row is used by a node instance to determine its node identity.

The following SQL statements set up a top-level registration server as a node identified as "00000" in the "corp" node group.

 insert into SYM_NODE (node_id,
node_group_id, external_id, sync_enabled) values ('00000', 'corp',
'00000', 1); insert into SYM_NODE_IDENTITY values ('00000');

The second table, NODE_SECURITY has rows created for each child node that registers with the node, assuming auto-registration is enabled. If auto registration is not enabled, you must create a row in NODE and NODE_SECURITY for the node to be able to register. You can also, with this table, manually cause a node to re-register or do a re-initial load by setting the corresponding columns in the table itself. Registration is discussed in more detail in Section 4.7, “Opening Registration” .

4.3. Node Group

Node Groups are straightforward to configure and are defined in the NODE_GROUP table. The following SQL statements would create node groups for "corp" and "store" based on our retail store example.

 insert into SYM_NODE_GROUP
(node_group_id, description) values ('store', 'A retail store node');

insert into SYM_NODE_GROUP (node_group_id, description) values ('corp',
'A corporate node');

4.4. Node Group Link

Similarly, Node Group links are established using a data event action of 'P' for Push and 'W' for Pull ("wait"). The following SQL statements links the "corp" and "store" node groups for synchronization. It configures the "store" nodes to push their data changes to the "corp" nodes, and the "corp" nodes to send changes to "store" nodes by waiting for a pull.

 insert into SYM_NODE_GROUP_LINK
(source_node_group, target_node_group, data_event_action) values
('store', 'corp', 'P'); insert into SYM_NODE_GROUP_LINK
(source_node_group, target_node_group, data_event_action) values
('corp', 'store', 'W');

A node group link can be configured to use the same node group as the source and the target. This configuration allows a node group to sync with every other node in its group.

A third type of link action of 'R' for 'Route Only' exists if you want to associate a router with a link that will not move the data. This action type might be useful when using an XML publishing router or an audit table changes router.

4.5. Channel

By categorizing data into channels and assigning them to TRIGGER s, the user gains more control and visibility into the flow of data. In addition, SymmetricDS allows for synchronization to be enabled, suspended, or scheduled by channels as well. The frequency of synchronization and order that data gets synchronized is also controlled at the channel level.

The following SQL statements setup channels for a retail store. An "item" channel includes data for items and their prices, while a "sale_transaction" channel includes data for ringing sales at a register.

 insert into SYM_CHANNEL (channel_id,
processing_order, max_batch_size, max_batch_to_send,
extract_period_millis, batch_algorithm, enabled, description) values
('item', 10, 1000, 10, 0, 'default', 1, 'Item and pricing data'); insert
into SYM_CHANNEL (channel_id, processing_order, max_batch_size,
max_batch_to_send, extract_period_millis, batch_algorithm, enabled,
description) values ('sale_transaction', 1, 1000, 10, 60000,
'transactional', 1, 'retail sale transactions from register');

Batching is the grouping of data, by channel, to be transferred and committed at the client together. There are three different out-of-the-box batching algorithms which may be configured in the batch_algorithm column on channel.

default

All changes that happen in a transaction are guaranteed to be batched together. Multiple transactions will be batched and committed together until there is no more data to be sent or the max_batch_size is reached.

transactional

Batches will map directly to database transactions. If there are many small database transactions, then there will be many batches. The max_batch_size column has no effect.

nontransactional

Multiple transactions will be batched and committed together until there is no more data to be sent or the max_batch_size is reached. The batch will be cut off at the max_batch_size regardless of whether it is in the middle of a transaction.

If a channel contains only tables that will be synchronized in one direction and and data is routed to all the nodes in the target node groups, then batching on the channel can be optimized to share batches across nodes. This is an important feature when data needs to be routed to thousands of nodes. When this mode is detected, you will see batches created in OUTGOING_BATCH with the common_flag set to 1.

There are also several size-related parameters that can be set by channel. They include:

max_batch_size

Specifies the maximum number of data events to process within a batch for this channel.

max_batch_to_send

Specifies the maximum number of batches to send for a given channel during a 'synchronization' between two nodes. A 'synchronization' is equivalent to a push or a pull. For example, if there are 12 batches ready to be sent for a channel and max_batch_to_send is equal to 10, then only the first 10 batches will be sent even though 12 batches are ready.

max_data_to_route

Specifies the maximum number of data rows to route for a channel at a time.

Based on your particular synchronization requirements, you can also specify whether old, new, and primary key data should be read and included during routing for a given channel. These are controlled by the columns use_old_data_to_route, use_row_data_to_route, and use_pk_data_to_route, respectively. By default, they are all 1 (true).

Finally, if data on a particular channel contains big lobs, you can set the column contains_big_lob to 1 (true) to provide SymmetricDS the hint that the channel contains big lobs. Some databases have shortcuts that SymmetricDS can take advantage of if it knows that the lob columns in DATA aren't going to contain large lobs. The definition of how large a 'big' lob is varies from database to database.

4.6. Triggers, Routers, and Trigger / Routers Mappings

In order to synchronize data, you must define at least one trigger, at least one router, and provide at least one link between the two (known as a trigger-router).

4.6.1. Trigger

SymmetricDS captures synchronization data using database triggers. SymmetricDS' Triggers are defined in the TRIGGER table. Each record is used by SymmetricDS when generating database triggers. Database triggers are only generated when a trigger is associated with a ROUTER whose source_node_group_id matches the node group id of the current node.

The source_table_name may contain the asterisk ('*') wildcard character so that one TRIGGER table entry can define synchronization for many tables. System tables and any tables that start with the SymmetricDS table prefix will be excluded. A list of wildcard tokens can also be supplied. If there are multiple tokens, they should be delimited with a comma. A wildcard token can also start with a bang ('!') to indicate an exclusive match. Tokens are always evalulated from left to right. When a table match is made, the table is either added to or removed from the list of tables. If another trigger already exists for a table, then that table is not included in the wildcard match (the explictly defined trigger entry take precendence).

When determining whether a data change has occurred or not, by defalt the triggers will record a change even if the data was updated to the same value(s) they were originally. For example, a data change will be captured if an update of one column in a row updated the value to the same value it already was. There is a global property, trigger.update.capture.changed.data.only.enabled (false by default), that allows you to override this behavior. When set to true, SymmetricDS will only capture a change if the data has truly changed (i.e., when the new column data is not equal to the old column data).

Important

The property trigger.update.capture.changed.data.only.enabled is currently only supported in the MySQL, DB2 and Oracle dialects.

The following SQL statement defines a trigger that will capture data for a table named "item" whenever data is inserted, updated, or deleted. The trigger is assigned to a channel also called 'item'.

 insert into SYM_TRIGGER
(trigger_id,source_table_name,channel_id,last_update_time,create_time)
values ('item', 'item', 'item', current_timestamp, current_timestamp); 

Important

Note that many databases allow for multiple triggers of the same type to be defined. Each database defines the order in which the triggers fire differently. If you have additional triggers beyond those SymmetricDS installs on your table, please consult your database documentation to determine if there will be issues with the ordering of the triggers.

4.6.1.1. Large Objects

Two lobs-related settings are also available on TRIGGER :

use_stream_lobs

Specifies whether to capture lob data as the trigger is firing or to stream lob columns from the source tables using callbacks during extraction. A value of 1 indicates to stream from the source via callback; a value of 0, lob data is captured by the trigger.

use_capture_lobs

Provides a hint as to whether this trigger will capture big lobs data. If set to 1 every effort will be made during data capture in trigger and during data selection for initial load to use lob facilities to extract and store data in the database.

4.6.1.2. External Select

Occasionally, you may find that you need to capture and save away a piece of data present in another table when a trigger is firing. This data is typically needed for the purposes of determining where to 'route' the data to once routing takes place. Each trigger definition contains an optional external_select field which can be used to specify the data to be captured. Once captured, this data is available during routing in DATA 's external_data field. For these cases, place a SQL select statement which returns the data item you need for routing in external_select . An example of the use of external select can be found in Section 4.6.2.7, “Utilizing External Select when Routing” .

4.6.2. Router

Routers provided in the base implementation currently include:

  • Default Router - a router that sends all data to all nodes that belong to the target node group defined in the router.
  • Column Match Router - a router that compares old or new column values to a constant value or the value of a node's external_id or node_id.
  • Lookup Router - a router which can be configured to determine routing based on an existing or ancillary table specifically for the purpose of routing data.
  • Subselect Router - a router that executes a SQL expression against the database to select nodes to route to. This SQL expression can be passed values of old and new column values.
  • Scripted Router - a router that executes a Bean Shell script expression in order to select nodes to route to. The script can use the old and new column values.
  • Xml Publishing Router - a router the publishes data changes directly to a messaging solution instead of transmitting changes to registered nodes. This router must be configured manually in XML as an extension point.
  • Audit Table Router - a router that inserts into an automatically created audit table. It records captured changes to tables that it is linked to.

The mapping between the set of triggers and set of routers is many-to-many. This means that one trigger can capture changes and route to multiple locations. It also means that one router can be defined an associated with many different triggers.

4.6.2.1. Default Router

The simplest router is a router that sends all the data that is captured by its associated triggers to all the nodes that belong to the target node group defined in the router. A router is defined as a row in the ROUTER table. It is then linked to triggers in the TRIGGER_ROUTER table.

The following SQL statement defines a router that will send data from the 'corp' group to the 'store' group.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, create_time,
last_update_time) values ('corp-2-store','corp', 'store',
current_timestamp, current_timestamp); 

The following SQL statement maps the 'corp-2-store' router to the item trigger.

 insert into SYM_TRIGGER_ROUTER
(trigger_id, router_id, initial_load_order, create_time,
last_update_time) values ('item', 'corp-2-store', 1, current_timestamp,
current_timestamp); 

4.6.2.2. Column Match Router

Sometimes requirements may exist that require data to be routed based on the current value or the old value of a column in the table that is being routed. Column routers are configured by setting the router_type column on the ROUTER table to column and setting the router_expression column to an equality expression that represents the expected value of the column.

The first part of the expression is always the column name. The column name should always be defined in upper case. The upper case column name prefixed by OLD_ can be used for a comparison being done with the old column data value.

The second part of the expression can be a constant value, a token that represents another column, or a token that represents some other SymmetricDS concept. Token values always begin with a colon (:).

Consider a table that needs to be routed to all nodes in the target group only when a status column is set to 'READY TO SEND.' The following SQL statement will insert a column router to accomplish that.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-ok','corp', 'store', 'column', 'STATUS=READY TO SEND',
current_timestamp, current_timestamp); 

Consider a table that needs to be routed to all nodes in the target group only when a status column changes values. The following SQL statement will insert a column router to accomplish that. Note the use of OLD_STATUS, where the OLD_ prefix gives access to the old column value.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-status','corp', 'store', 'column', 'STATUS!=:OLD_STATUS',
current_timestamp, current_timestamp); 

Consider a table that needs to be routed to only nodes in the target group whose STORE_ID column matches the external id of a node. The following SQL statement will insert a column router to accomplish that.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-id','corp', 'store', 'column', 'STORE_ID=:EXTERNAL_ID',
current_timestamp, current_timestamp); 

Attributes on a NODE that can be referenced with tokens include:

  • :NODE_ID
  • :EXTERNAL_ID
  • :NODE_GROUP_ID

Captured EXTERNAL_DATA is also available for routing as a virtual column.

Consider a table that needs to be routed to a redirect node defined by its external id in the REGISTRATION_REDIRECT table. The following SQL statement will insert a column router to accomplish that.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-redirect','corp', 'store', 'column',
'STORE_ID=:REDIRECT_NODE', current_timestamp, current_timestamp); 

More than one column may be configured in a router_expression. When more than one column is configured, all matches are added to the list of nodes to route to. The following is an example where the STORE_ID column may contain the STORE_ID to route to or the constant of ALL which indicates that all nodes should receive the update.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-multiple-matches','corp', 'store', 'column',
'STORE_ID=ALL or STORE_ID=:EXTERNAL_ID', current_timestamp,
current_timestamp); 

The NULL keyword may be used to check if a column is null. If the column is null, then data will be routed to all nodes who qualify for the update. This following is an example where the STORE_ID column is used to route to a set of nodes who have a STORE_ID equal to their EXTERNAL_ID, or to all nodes if the STORE_ID is null.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-multiple-matches','corp', 'store', 'column',
'STORE_ID=NULL or STORE_ID=:EXTERNAL_ID', current_timestamp,
current_timestamp); 

4.6.2.3. Lookup Table Router

A lookup table may contain the id of the node where data needs to be routed. This could be an existing table or an ancillary table that is added specifically for the purpose of routing data. Lookup table routers are configured by setting the router_type column on the ROUTER table to lookuptable and setting a list of configuration parameters in the router_expression column.

Each of the following configuration parameters are required.

LOOKUP_TABLE

This is the name of the lookup table.

KEY_COLUMN

This is the name of the column on the table that is being routed. It will be used as a key into the lookup table.

LOOKUP_KEY_COLUMN

This is the name of the column that is the key on the lookup table.

EXTERNAL_ID_COLUMN

This is the name of the column that contains the external_id of the node to route to on the lookup table.

Note that the lookup table will be read into memory and cached for the duration of a routing pass for a single channel.

Consider a table that needs to be routed to a specific store, but the data in the changing table only contains brand information. In this case, the STORE table may be used as a lookup table.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-ok','corp', 'store', 'lookuptable', 'LOOKUP_TABLE=STORE
KEY_COLUMN=BRAND_ID LOOKUP_KEY_COLUMN=BRAND_ID
EXTERNAL_ID_COLUMN=STORE_ID', current_timestamp, current_timestamp); 

4.6.2.4. Subselect Router

Sometimes routing decisions need to be made based on data that is not in the current row being synchronized. A 'subselect' router can be used in these cases. A 'subselect' is configured with a router_expression that is a SQL select statement which returns a result set of the node ids that need routed to. Column tokens can be used in the SQL expression and will be replaced with row column data. The overhead of using this router type is high because the 'subselect' statement runs for each row that is routed. It should not be used for tables that have a lot of rows that are updated. It also has the disadvantage that if the data being relied on to determine the node id has been deleted before routing takes place, then no results would be returned and routing would not happen.

The router_expression you specify is appended to the following SQL statement in order to select the node ids:

select c.node_id from sym_node c where
c.node_group_id=:NODE_GROUP_ID and c.sync_enabled=1 and ... 

As you can see, you have access to information about the node currently under consideration for routing through the 'c' alias, for example c.external_id . There are two node-related tokens you can use in your expression:

  • :NODE_GROUP_ID
  • :EXTERNAL_DATA

Column names representing data for the row in question are prefixed with a colon as well, for example: :EMPLOYEE_ID , or :OLD_EMPLOYEE_ID . Here, the OLD_ prefix indicates the value before the change in cases where the old data has been captured.

For an example, consider the case where an Order table and an OrderLineItem table need to be routed to a specific store. The Order table has a column named order_id and STORE_ID. A store node has an external_id that is equal to the STORE_ID on the Order table. OrderLineItem, however, only has a foreign key to its Order of order_id. To route OrderLineItems to the same nodes that the Order will be routed to, we need to reference the master Order record.

There are two possible ways to solve this in SymmetricDS. One is to configure a 'subselect' router_type on the ROUTER table, shown below (The other possible approach is to use an external_select to capture the data via a trigger for use in a column match router, demonstrated in Section 4.6.2.7, “Utilizing External Select when Routing” ).

Our solution utilizing subselect compares the external id of the current node with the store id from the Order table where the order id matches the order id of the current row being routed:

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store','corp', 'store', 'subselect', 'c.external_id in (select
STORE_ID from order where order_id=:ORDER_ID)', current_timestamp,
current_timestamp); 

As a final note, please note in this example that the parent row in Order must still exist at the moment of routing for the child rows (OrderLineItem) to route, since the select statement is run when routing is occurring, not when the change data is first captured.

4.6.2.5. Scripted Router

When more flexibility is needed in the logic to choose the nodes to route to, then the a scripted router may be used. The currently available scripting language is Bean Shell. Bean Shell is a Java-like scripting language. Documentation for the Bean Shell scripting language can be found at http://www.beanshell.org .

The router_type for a Bean Shell scripted router is 'bsh'. The router_expression is a valid Bean Shell script that:

  • adds node ids to the targetNodes collection which is bound to the script
  • returns a new collection of node ids
  • returns a single node id
  • returns true to indicate that all nodes should be routed or returns false to indicate that no nodes should be routed

Also bound to the script evaluation is a list of nodes . The list of nodes is a list of eligible org.jumpmind.symmetric.model.Node objects. The current data column values and the old data column values are bound to the script evaluation as Java object representations of the column data. The columns are bound using the uppercase names of the columns. Old values are bound to uppercase representations that are prefixed with 'OLD_'.

If you need access to any of the SymmetricDS services, then the instance of org.jumpmind.symmetric.ISymmetricEngine is accessible via the bound engine variable.

In the following example, the node_id is a combination of STORE_ID and WORKSTATION_NUMBER, both of which are columns on the table that is being routed.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-bsh','corp', 'store', 'bsh', 'targetNodes.add(STORE_ID +
"-" + WORKSTATION_NUMBER);', current_timestamp, current_timestamp); 

The same could also be accomplished by simply returning the node id. The last line of a bsh script is always the return value.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-bsh','corp', 'store', 'bsh', 'STORE_ID + "-" +
WORKSTATION_NUMBER', current_timestamp, current_timestamp); 

The following example will synchronize to all nodes if the FLAG column has changed, otherwise no nodes will be synchronized. Note that here we make use of OLD_, which provides access to the old column value.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-flag-changed','corp', 'store', 'bsh', 'FLAG != null
&& !FLAG.equals(OLD_FLAG)', current_timestamp,
current_timestamp); 

The next example shows a script that iterates over each eligible node and checks to see if the trimmed value of the column named STATION equals the external_id.

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-trimmed-station','corp', 'store', 'bsh', 'for
(org.jumpmind.symmetric.model.Node node : nodes) { if (STATION != null
&& node.getExternalId().equals(STATION.trim())) {
targetNodes.add(node.getNodeId()); } }', current_timestamp,
current_timestamp); 

4.6.2.6. Audit Table Router

This router audits captured data by recording the change in an audit table that the router creates and keeps up to date (as long as auto.config.database is set to true.) The router creates a table named the same as the table for which data was captured with the suffix of _AUDIT. It will contain all of the same columns as the original table with the same data types only each column is nullable with no default values.

Three extra "AUDIT" columns are added to the table:

  • AUDIT_ID - the primary key of the table.
  • AUDIT_TIME - the time at which the change occurred.
  • AUDIT_EVENT - the DML type that happened to the row.

The following is an example of an audit router

 insert into SYM_ROUTER (router_id,
source_node_group_id, target_node_group_id, router_type, create_time,
last_update_time) values ('audit_at_corp','corp', 'local', 'audit',
current_timestamp, current_timestamp); 

The audit router captures data for a group link. For the audit router to work it must be associated with a node_group_link with an action of type 'R'. The 'R' stands for 'only routes to'. In the above example, we refer to a 'corp to local' group link. Here, local is a new node_group created for the audit router. No nodes belong to the 'local' node_group. If a trigger linked to an audit router fires on the corp node, a new audit table will be created at the corp node with the new data inserted.

4.6.2.7. Utilizing External Select when Routing

There may be times when you wish to route based on a piece of data that exists in a table other than the one being routed. The approach, first discussed in Section 4.6.2.4, “Subselect Router” , is to utilize an external_select to save away data in external_data , which can then be referenced during routing.

Reconsider subselect's Order / OrderLineItem example (found in Section 4.6.2.4, “Subselect Router” ), where routing for the line item is accomplished by linking to the "header" Order row. As an alternate way of solving the problem, we will now use External Select combined with a column match router.

In this version of the solution, the STORE_ID is captured from the Order table in the EXTERNAL_DATA column when the trigger fires. The router is configured to route based on the captured EXTERNAL_DATA to all nodes whose external id matches the captured external data.

insert into SYM_TRIGGER
(trigger_id,source_table_name,channel_id,external_select,
last_update_time,create_time) values ('orderlineitem', 'orderlineitem',
'orderlineitem','select STORE_ID from order where
order_id=$(curTriggerValue).$(curColumnPrefix)order_id',
current_timestamp, current_timestamp); insert into SYM_ROUTER
(router_id, source_node_group_id, target_node_group_id, router_type,
router_expression, create_time, last_update_time) values
('corp-2-store-ext','corp', 'store', 'column',
'EXTERNAL_DATA=:EXTERNAL_ID', current_timestamp, current_timestamp); 

The following variables can be used with the external select:

$(curTriggerValue)

Variable to be replaced with the NEW or OLD column alias provided by the trigger context, which is platform specific. For insert and update triggers, the NEW alias is used; for delete triggers, the OLD alias is used. For example, "$(curTriggerValue).COLUMN" becomes ":new.COLUMN" for an insert trigger on Oracle.

$(curColumnPrefix)

Variable to be replaced with the NEW_ or OLD_ column prefix for platforms that don't support column aliases. This is currently only used by the H2 database. All other platforms will replace the variable with an empty string. For example "$(curColumnPrefix)COLUMN" becomes "NEW_COLUMN" on H2 and "COLUMN" on Oracle.

The advantage of this approach over the 'subselect' approach is that it guards against the (somewhat unlikely) possibility that the master Order table row might have been deleted before routing has taken place. This external select solution also is a bit more efficient than the 'subselect' approach, although the triggers produced do run the extra external_select SQL inline with application database updates.

4.6.3. Trigger / Router Mappings

The TRIGGER_ROUTER table is used to define which specific combinations of triggers and routers are needed for your configuration. The relationship between triggers and routers is many-to-many, so this table serves as the join table to define which combinations are valid, as well as to define settings available at the trigger-router level of granularity.

Three important controls can be configured for a specific Trigger / Router combination: Enabled, Initial Loads and Ping Back. The parameters for these can be found in the Trigger / Router mapping table, TRIGGER_ROUTER .

4.6.3.1. Enable / disable trigger router

Each individual trigger-router combination can be disabled or enabled if needed. By default, a trigger router is enabled, but if you have a reason you wish to define a trigger router combination prior to it being active, you can set the enabled flag to 0. This will cause the trigger-router mapping to be sent to all nodes, but the trigger-router mapping will not be considered active or enabled for the purposes of capturing data changes or routing.

4.6.3.2. Initial Loads

An initial load is the process of seeding tables at a target node with data from its parent node. When a node connects and data is extracted, after it is registered and if an initial load was requested, each table that is configured to synchronize to the target node group will be given a reload event in the order defined by the end user. A SQL statement is run against each table to get the data load that will be streamed to the target node. The selected data is filtered through the configured router for the table being loaded. If the data set is going to be large, then SQL criteria can optionally be provided to pare down the data that is selected out of the database.

An initial load cannot occur until after a node is registered. An initial load is requested by setting the initial_load_enabled column on NODE_SECURITY to 1 on the row for the target node in the parent node's database. You can configure SymmetricDS to automatically perform an initial load when a node registers by setting the parameter auto.reload to true. Regardless of how the initial load is initiated, the next time the source node routes data, reload batches will be inserted. At the same time reload batches are inserted, all previously pending batches for the node are marked as successfully sent.

Important

Note that if the parent node that a node is registering with is not a registration server node (as can happen with a registration redirect or certain non-tree structure node configurations) the parent node's NODE_SECURITY entry must exist at the parent node and have a non-null value for column initial_load_time . Nodes can't be registered to non-registration-server nodes without this value being set one way or another (i.e., manually, or as a result of an initial load occurring at the parent node).

SymmetricDS recognizes that an initial load has completed when the initial_load_time column on the target node is set to a non-null value.

An initial load is accomplished by inserting reload batches in a defined order according to the initial_load_order column on TRIGGER_ROUTER . If the initial_load_order column contains a negative value the associated table will NOT be loaded. If the initial_load_order column contains the same value for multiple tables, SymmetricDS will attempt to order the tables according to foreign key constraints. If there are cyclical constraints, then foreign keys might need to be turned off or the initial load will need to be manually configured based on knowledge of how the data is structured.

Initial load data is always queried from the source database table. All data is passed through the configured router to filter out data that might not be targeted at a node.

Target table prep for initial load

There are several parameters that can be used to specify what, if anything, should be done to the table on the target database just prior to loading the data. Note that the parameters below specify the desired behavior for all tables in the initial load, not just one.

  • initial.load.delete.first / initial.load.delete.first.sql

    By default, an initial load will not delete existing rows from a target table before loading the data. If a delete is desired, the parameter initial.load.delete.first can be set to true. If true, the command found in initial.load.delete.first.sql will be run on each table prior to loading the data. The default value for initial.load.delete.first.sql is delete from %s , but could be changed if needed. Note that additional reload batches are created, in the correct order, to achieve the delete.

  • initial.load.create.first

    By default, an initial load will not create the table on the target if it doesn't alleady exist. If the desired behavior is to create the table on the target if it is not present, set the parameter intial.load.create.first to true. SymmetricDS will attempt to create the table and indexes on the target database before doing the initial load. (Additional batches are created to represent the table schema).

Loading subsets of data

An efficient way to select a subset of data from a table for an initial load is to provide an initial_load_select clause on TRIGGER_ROUTER . This clause, if present, is applied as a where clause to the SQL used to select the data to be loaded. The clause may use "t" as an alias for the table being loaded, if needed. The $(externalId) token can be used for subsetting the data in the where clause.

In cases where routing is done using a feature like Section 4.6.2.4, “Subselect Router” , an initial_load_select clause matching the subselect's criteria would be a more efficient approach. Some routers will check to see if the initial_load_select clause is provided, and they will not execute assuming that the more optimal path is using the initial_load_select statement.

One example of the use of an initial load select would be if you wished to only load data created more recently than the start of year 2011. Say, for example, the column created_time contains the creation date. Your initial_load_select would read created_time > ts {'2011-01-01 00:00:00.0000'} (using whatever timestamp format works for your database). This then gets applied as a where clause when selecting data from the table.

Important

When providing an initial_load_select be sure to test out the criteria against production data in a query browser. Do an explain plan to make sure you are properly using indexes.

Splitting an Initial Load for a Table Across Multiple Batches

By default, all data for a given table will be initial loaded in a single batch, regardless of the max batch size parameter on the reload channel. That is, for a table with one million rows, all rows for that table will be initial loaded and sent to the destination node in a single batch. For large tables, this can result in a batch that can take a long time to extract and load.

Initial loads for a table can be broken into multiple batches by specifying initial.load.use.extract.job.enabled to true. This parameter allows SymmetricDS to pre-extract initial load batches versus having them extracted when the batch is pulled or pushed. When using this parameter, there are two ways to tell SymmetricDS the number of batches to create for a given table. The first is to specify a positive integer in the initial_load_batch_count column on TRIGGER_ROUTER. This number will dictate the number of batches created for the initial load of the given table. The second way is to specify 0 for initial_load_batch_count on TRIGGER_ROUTER and specify a max_batch_size on the reload channel in CHANNEL. When 0 is specified for initial_load_batch_count, SymmetricDS will execute a count(*) query on the table during the extract process and create N batches based on the total number of records found in the table divided by the max_batch_size on the reload channel.

Reverse Initial Loads

The default behavior for initial loads is to load data from the registration server or parent node, to a client node. Occasionally, there may be need to do a one-time intial load of data in the opposite or "reverse" direction, namely from a client node to the registration node. To achieve this, set the parameter auto.reload.reverse to be true, but only for the specific node group representing the client nodes . This will cause a onetime reverse load of data, for tables configured with non-negative initial load orders, to be batched at the point when registration of the client node is occurring. These batches are then sent to the parent or registration node. This capability might be needed, for example, if there is data already present in the client that doesn't exist in the parent but needs to.

4.6.3.3. Dead Triggers

Occasionally the decision of what data to load initially results in additional triggers. These triggers, known as Dead Triggers , are configured such that they do not capture any data changes. A "dead" Trigger is one that does not capture data changes. In other words, the sync_on_insert , sync_on_update , and sync_on_delete properties for the Trigger are all set to false. However, since the Trigger is specified, it will be included in the initial load of data for target Nodes.

Why might you need a Dead Trigger? A dead Trigger might be used to load a read-only lookup table, for example. It could also be used to load a table that needs populated with example or default data. Another use is a recovery load of data for tables that have a single direction of synchronization. For example, a retail store records sales transactions that synchronize in one direction by trickling back to the central office. If the retail store needs to recover all the sales transactions from the central office, they can be sent are part of an initial load from the central office by setting up dead Triggers that "sync" in that direction.

The following SQL statement sets up a non-syncing dead Trigger that sends the sale_transaction table to the "store" Node Group from the "corp" Node Group during an initial load.

 insert into sym_trigger
(TRIGGER_ID,SOURCE_CATALOG_NAME,
SOURCE_SCHEMA_NAME,SOURCE_TABLE_NAME,CHANNEL_ID,
SYNC_ON_UPDATE,SYNC_ON_INSERT,SYNC_ON_DELETE,
SYNC_ON_INCOMING_BATCH,NAME_FOR_UPDATE_TRIGGER,
NAME_FOR_INSERT_TRIGGER,NAME_FOR_DELETE_TRIGGER,
SYNC_ON_UPDATE_CONDITION,SYNC_ON_INSERT_CONDITION,
SYNC_ON_DELETE_CONDITION,EXTERNAL_SELECT,
TX_ID_EXPRESSION,EXCLUDED_COLUMN_NAMES,
CREATE_TIME,LAST_UPDATE_BY,LAST_UPDATE_TIME) values
('SALE_TRANSACTION_DEAD',null,null, 'SALE_TRANSACTION','transaction',
0,0,0,0,null,null,null,null,null,null,null,null,null,
current_timestamp,'demo',current_timestamp); insert into sym_router
(ROUTER_ID,TARGET_CATALOG_NAME,TARGET_SCHEMA_NAME,
TARGET_TABLE_NAME,SOURCE_NODE_GROUP_ID,TARGET_NODE_GROUP_ID,ROUTER_TYPE,
ROUTER_EXPRESSION,SYNC_ON_UPDATE,SYNC_ON_INSERT,SYNC_ON_DELETE,
CREATE_TIME,LAST_UPDATE_BY,LAST_UPDATE_TIME) values
('CORP_2_STORE',null,null,null, 'corp','store',null,null,1,1,1,
current_timestamp,'demo',current_timestamp); insert into
sym_trigger_router (TRIGGER_ID,ROUTER_ID,INITIAL_LOAD_ORDER,
INITIAL_LOAD_SELECT,CREATE_TIME,LAST_UPDATE_BY,LAST_UPDATE_TIME) values
('SALE_TRANSACTION_DEAD','CORP_2_REGION',100,null,
current_timestamp,'demo',current_timestamp); 

4.6.3.4. Enabling "Ping Back"

As discussed in Section 3.6.3.2, “Circular References and "Ping Back"” SymmetricDS, by default, avoids circular data changes. When a trigger fires as a result of SymmetricDS itself (such as the case when sync on incoming batch is set), it records the originating source node of the data change in source_node_id . During routing, if routing results in sending the data back to the originating source node, the data is not routed by default. If instead you wish to route the data back to the originating node, you can set the ping_back_enabled column for the needed particular trigger / router combination. This will cause the router to "ping" the data back to the originating node when it usually would not.

4.7. Opening Registration

Node registration is the act of setting up a new NODE and NODE_SECURITY so that when the new node is brought online it is allowed to join the system. Nodes are only allowed to register if rows exist for the node and the registration_enabled flag is set to 1. If the auto.registration SymmetricDS property is set to true, then when a node attempts to register, if registration has not already occurred, the node will automatically be registered.

SymmetricDS allows you to have multiple nodes with the same external_id . Out of the box, openRegistration will open a new registration if a registration already exists for a node with the same external_id. A new registration means a new node with a new node_id and the same external_id will be created. If you want to re-register the same node you can use the reOpenRegistration() JMX method which takes a node_id as an argument.

4.8. Transforming Data

New as of SymmetricDS 2.4, SymmetricDS is now able to transform synchronized data by way of configuration (previously, for most cases a custom data loader would need to have been written). This transformation can take place on a source node or on a target node, as the data is being loaded or extracted. With this new feature you can, for example:

  • Copy a column from a source table to two (or more) target table columns,

  • Merge columns from two or more source tables into a single row in a target table,

  • Insert constants in columns in target tables based on source data synchronizations,

  • Insert multiple rows of data into a single target table based on one change in a source table,

  • Apply a Bean Shell script to achieve a custom transform when loading into the target database.

These transformations can take place either on the target or on the source, and as data is either being extracted or loaded. In either case, the transformation is initiated due to existence of a source synchronization trigger. The source trigger creates the synchronization data, while the transformation configuration decides what to do with the synchronization data as it is either being extracted from the source or loaded into the target. You have the flexibility of defining different transformation behavior depending on whether the source change that triggered the synchronization was an Insert, Update, or Delete. In the case of Delete, you even have options on what exactly to do on the target side, be it a delete of a row, setting columns to specific values, or absolutely nothing at all.

A few key concepts are important to keep in mind to understand how SymmetricDS performs transformations. The first concept is that of the "source operation" or "source DML type", which is the type of operation that occurred to generate the synchronization data in the first place (i.e., an insert, a delete, or an update). Your transformations can be configured to act differently based on the source DML type, if desired. When transforming, by default the DML action taken on the target matches that of the action taken on the row in the source (although this behavior can be altered through configuration if needed). If the source DML type is an Insert, for example, the resulting transformation DML(s) will be Insert(s).

Another important concept is the way in which transforms are applied. Each source operation may map to one or more transforms and result in one or more operations on the target tables. Each of these target operations are performed as independent operations in sequence and must be "complete" from a SQL perspective. In other words, you must define columns for the transformation that are sufficient to fill in any primary key or other required data in the target table if the source operation was an Insert, for example.

Finally, please note that the transformation engine relies on a source trigger / router existing to supply the source data for the transformation. The transform configuration will never be used if the source table and target node group does not have a defined trigger / router combination for that source table and target node group.

4.8.1. Transform Configuration Tables

SymmetricDS stores its transformation configuration in two configuration tables, TRANSFORM_TABLE and TRANSFORM_COLUMN . Defining a transformation involves configuration in both tables, with the first table defining which source and destination tables are involved, and the second defining the columns involved in the transformation and the behavior of the data for those columns. We will explain the various options available in both tables and the various pre-defined transformation types.

To define a transformation, you will first define the source table and target table that applies to a particular transformation. The source and target tables, along with a unique identifier (the transform_id column) are defined in TRANSFORM_TABLE . In addition, you will specify the source_node_group_id and target_node_group_id to which the transform will apply, along with whether the transform should occur on the Extract step or the Load step (transform_point). All of these values are required.

Three additional configuration settings are also defined at the source-target table level: the order of the transformations, the behavior when deleting, and whether an update should always be attempted first. More specifically,

  • transform_order: For a single source operation that is mapped to a transformation, there could be more than one target operation that takes place. You may control the order in which the target operations are applied through a configuration parameter defined for each source-target table combination. This might be important, for example, if the foreign key relationships on the target tables require you to execute the transformations in a particular order.
  • column_policy: Indicates whether unspecified columns are passed thru or if all columns must be explicitly defined. The options include:
    • SPECIFIED - Indicates that only the transform columns that are defined will be the ones that end up as part of the transformation.
    • IMPLIED - Indicates that if not specified, then columns from the source are passed through to the target. This is useful if you just want to map a table from one name to anther or from one schema to another. It is also useful if you want to transform a table, but also want to pass it through. You would define an implied transform from the source to the target and would not have to configure each column.
  • delete_action: When a source operation of Delete takes place, there are three possible ways to handle the transformation at the target. The options include:
    • NONE - The delete results in no target changes.
    • DEL_ROW - The delete results in a delete of the row as specified by the pk columns defined in the transformation configuration.
    • UPDATE_COL - The delete results in an Update operation on the target which updates the specific rows and columns based on the defined transformation.
  • update_first: This option overrides the default behavior for an Insert operation. Instead of attempting the Insert first, SymmetricDS will always perform an Update first and then fall back to an Insert if that fails. Note that, by default, fall back logic always applies for Insert and Updates. Here, all you a specifying is whether to always do an Update first, which can have performance benefits under certain situations you may run into.

For each transformation defined in TRANSFORM_TABLE , the columns to be transformed (and how they are transformed) are defined in TRANSFORM_COLUMN . This column-level table typically has several rows for each transformation id, each of which defines the source column name, the target column name, as well as the following details:

  • include_on: Defines whether this entry applies to source operations of Insert (I), Update (U), or Delete (D), or any source operation.
  • pk: Indicates that this mapping is used to define the "primary key" for identifying the target row(s) (which may or may not be the true primary key of the target table). This is used to define the "where" clause when an Update or Delete on the target is occurring. At least one row marked as a pk should be present for each transform_id.
  • transform_type, transform_expression: Specifies how the data is modified, if at all. The available transform types are discussed below, and the default is 'copy', which just copies the data from source to target.
  • transform_order: In the event there are more than one columns to transform, this defines the relative order in which the transformations are applied.

4.8.2. Transformation Types

There are several pre-defined transform types available in SymmetricDS. Additional ones can be defined by creating and configuring an extension point which implements the IColumnTransform interface. The pre-defined transform types include the following (the transform_type entry is shown in parentheses):

  • Copy Column Transform ('copy'): This transformation type copies the source column value to the target column. This is the default behavior.
  • Remove Column Transform ('remove'): This transformation type removes the source column. This transform type is only valid for a table transformation type of 'IMPLIED' where all the columns from the source are automatically copied to the target.
  • Constant Transform ('const'): This transformation type allows you to map a constant value to the given target column. The constant itself is placed in transform_expression.
  • Variable Transform ('variable'): This transformation type allows you to map a built-in dynamic variable to the given target column. The variable name is placed in transform_expression. The following variables are available: system_date is the current system date, system_timestamp is the current system date and time, source_node_id is the node id of the source, target_node_id is the node id of the target, null is a null value, and old_column_value is the column's old value prior to the DML operation.
  • Additive Transform ('additive'): This transformation type is used for numeric data. It computes the change between the old and new values on the source and then adds the change to the existing value in the target column. That is, target = target + multiplier (source_new - source_old), where multiplier is a constant found in the transform_expression (default is 1 if not specified). For example, if the source column changed from a 2 to a 4, the target column is currently 10, and the multiplier is 3, the effect of the transform will be to change the target column to a value of 16 ( 10+3*(4-2) => 16 ). Note that, in the case of deletes, the new column value is considered 0 for the purposes of the calculation.
  • Substring Transform ('substr'): This transformation computes a substring of the source column data and uses the substring as the target column value. The transform_expression can be a single integer ( n , the beginning index), or a pair of comma-separated integers ( n,m - the beginning and ending index). The transform behaves as the Java substring function would using the specified values in transform_expression.
  • Multiplier Transform ('multiply'): This transformation allows for the creation of multiple rows in the target table based on the transform_expression. This transform type can only be used on a primary key column. The transform_expression is a SQL statement that returns the list to be used to create the multiple targets.
  • Lookup Transform ('lookup'): This transformation determines the target column value by using a query, contained in transform_expression to lookup the value in another table. The query must return a single row, and the first column of the query is used as the value. Your query references source column names by prefixing with a colon (e.g., :MY_COLUMN).
  • Shell Script Transform ('bsh'): This transformation allows you to provide a Bean Shell script in transform_expression and executes the script at the time of transformation. Some variables are provided to the script: COLUMN_NAME is a variable for a source column in the row, where the variable name is the column name in uppercase; currentValue is the value of the current source column; oldValue is the old value of the source column for an updated row; sqlTemplate is a org.jumpmind.db.sql.ISqlTemplate object for querying or updating the database; channelId is a reference to the channel on which the transformation is happening; sourceNode is a org.jumpmind.symmetric.model.Node object that represents the node from where the data came; targetNode is a org.jumpmind.symmetric.model.Node object that represents the node where the data is being loaded.
  • Identity Transform ('identity'): This transformation allows you to insert into an identity column by computing a new identity, not copying the actual identity value from the source.
  • Mathematical Transform ('math'): This transformation allows you to perform mathematical equations in the transform expression. Some variables are provided to the script: #{COLUMN_NAME} is a variable for a source column in the row, where the variable name is the column name in uppercase; #{currentValue} is the value of the current source column; #{oldValue} is the old value of the source column for an updated row.
  • Value Map Transform ('valueMap'): This transformation allows for simple value substitutions through use of the transform expression. The transform expresion should consist of a space separated list of value pairs of the format sourceValue=TargetValue. The column value is used to locate the correct sourceValue, and the transform will change the value into the corresponding targetValue. A sourceValue of * can be used to represent a default target value in the event that the sourceValue is not found. Otherwise, if no default value is found, the result will be null. For example, consider the following transform expression: s1=t1 s2=t2 s3=t3 *=t4. A source value of s1 will be transformed to t1, s2 to t2, s3 to t3, s4 to t4, s5 to t4, null to t4, etc.

4.9. Data Load Filters

New as of SymmetricDS 3.1, SymmetricDS is now capable of taking actions upon the load of certain data via configurable load filters. This new configurable option is in additon to the already existing option of writing a class that implements IDatabaseWriterFilter . A configurable load filter watches for specific data that is being loaded and then takes action based on the load of that data.

Specifying which data to action is done by specifying a souce and target node group (data extracted from this node group, and loaded into that node group), and a target catalog, schema and table name. You can decide to take action on rows that are inserted, updated and/or deleted, and can also further delineate which rows of the target table to take action on by specifying additional criteria in the bean shell script that is executed in response to the loaded data. As an example, old and new values for the row of data being loaded are available in the bean shell script, so you can action rows with a certain column value in old or new data.

The action taken is based on a bean shell script that you can provide as part of the configuration. Actions can be taken at different points in the load process including before write, after write, at batch complete, at batch commit and/or at batch rollback.

4.9.1. Load Filter Configuration Table

SymmetricDS stores its load filter configuration in a single table called LOAD_FILTER . The load filter table allows you to specify the following:

  • Load Filter Type ('load_filter_type'): The type of load filter. Today only Bean Shell is supported ('BSH'), but SQL scripts may be added in a future release.
  • Source Node Group ('source_node_group_id'): The source node group for which you would like to watch for changes.
  • Target Node Group ('target_node_group_id'): The target node group for which you would like to watch for changes. The source and target not groups are used together to identify the node group link for which you would like to watch for changes (i.e. When the Server node group sends data to a Client node group).
  • Target Catalog ('target_catalog_name'): The name of the target catalog for which you would like to watch for changes.
  • Target Schema ('target_schema_name'): The name of the target schema for which you would like to watch for changes.
  • Target Table ('target_table_name'): The name of the target table for which you would like to watch for changes. The target catalog, target schema and target table name are used together to fully qualify the table for which you would like to watch for changes.
  • Filter on Update ('filter_on_update'): Determines whether the load filter takes action (executes) on a database update statement.
  • Filter on Insert ('filter_on_insert'): Determines whether the load filter takes action (executes) on a database insert statement.
  • Filter on Delete ('filter_on_delete'): Determines whether the load filter takes action (executes) on a database delete statement.
  • Before Write Script ('before_write_script'): The script to execute before the database write occurs.
  • After Write Script ('after_write_script'): The script to execute after the database write occurs.
  • Batch Complete Script ('batch_complete_script'): The script to execute after the entire batch completes.
  • Batch Commit Script ('batch_commit_script'): The script to execute after the entire batch is committed.
  • Batch Rollback Script ('batch_rollback_script'): The script to execute if the batch rolls back.
  • Handle Error Script ('handle_error_script'): A script to execute if data cannot be processed.
  • Load Filter Order ('load_filter_order'): The order in which load filters should execute if there are multiple scripts pertaining to the same source and target data.

4.9.2. Variables available to Data Load Filters

As part of the bean shell load filters, SymmetricDS provides certain variables for use in the bean shell script. Those variables include:

  • Symmetric Engine ('ENGINE'): The Symmetric engine object.
  • Source Values ('<COLUMN_NAME>'): The source values for the row being inserted, updated or deleted.
  • Old Values ('OLD_<COLUMN_NAME>'): The old values for the row being inserted, updated or deleted.
  • Data Context ('CONTEXT'): The data context object for the data being inserted, updated or deleted. .
  • Table Data ('TABLE'): The table object for the table being inserted, updated or deleted.

4.9.3. Data Load Filter Example

The following is an example of a load filter that watches a table named TABLE_TO_WATCH being loaded from the Server Node Group to the Client Node Group for inserts or updates, and performs an initial load on a table named "TABLE_TO_RELOAD" for KEY_FIELD on the reload table equal to a column named KEY_FIELD on the TABLE_TO_WATCH table.

 insert into sym_load_filter
(LOAD_FILTER_ID, LOAD_FILTER_TYPE, SOURCE_NODE_GROUP_ID,
TARGET_NODE_GROUP_ID, TARGET_CATALOG_NAME, TARGET_SCHEMA_NAME,
TARGET_TABLE_NAME, FILTER_ON_UPDATE, FILTER_ON_INSERT, FILTER_ON_DELETE,
BEFORE_WRITE_SCRIPT, AFTER_WRITE_SCRIPT, BATCH_COMPLETE_SCRIPT,
BATCH_COMMIT_SCRIPT, BATCH_ROLLBACK_SCRIPT, HANDLE_ERROR_SCRIPT,
CREATE_TIME, LAST_UPDATE_BY, LAST_UPDATE_TIME, LOAD_FILTER_ORDER,
FAIL_ON_ERROR) values
('TABLE_TO_RELOAD','BSH','Client','Server',NULL,NULL,
'TABLE_TO_WATCH',1,1,0,null,
'engine.getDataService().reloadTable(context.getBatch().getSourceNodeId(),
table.getCatalog(), table.getSchema(), "TABLE_TO_RELOAD","KEY_FIELD=''"
+ KEY_FIELD + "''");'
,null,null,null,null,sysdate,'userid',sysdate,1,1); 

4.10. Conflict Detection and Resolution

Conflict detection and resolution is new as of SymmetricDS 3.0. Conflict detection is the act of determining if an insert, update or delete is in "conflict" due to the target data row not being consistent with the data at the source prior to the insert/update/delete. Conflict resolution is the act of figuring out what to do when a conflict is detected.

Conflict detection and resolution strategies are configured in the CONFLICT table. They are configured at minimum for a specific NODE_GROUP_LINK . The configuration can also be specific to a CHANNEL and/or table.

Conflict detection is configured in the detect_type and detect_expression columns of CONFLICT . The value for detect_expression depends on the detect_type . Conflicts are detected while data is being loaded into a target system.

USE_PK_DATA

Indicates that only the primary key is used to detect a conflict. If a row exists with the same primary key, then no conflict is detected during an update or a delete. Updates and deletes rows are resolved using only the primary key columns. If a row already exists during an insert then a conflict has been detected.

USE_OLD_DATA

Indicates that all of the old data values are used to detect a conflict. Old data is the data values of the row on the source system prior to the change. If a row exists with the same old values on the target system as they were on the source system, then no conflict is detected during an update or a delete. If a row already exists during an insert then a conflict has been detected.

Note that some platforms do not support comparisons of binary columns. Conflicts in binary column values will not be detected on the following platforms: DB2, DERBY, ORACLE, and SQLSERVER.

USE_CHANGED_DATA

Indicates that the primary key plus any data that has changed on the source system will be used to detect a conflict. If a row exists with the same old values on the target system as they were on the source system for the columns that have changed on the source system, then no conflict is detected during an update or a delete. If a row already exists during an insert then a conflict has been detected.

Note that some platforms do not support comparisons of binary columns. Conflicts in binary column values will not be detected on the following platforms: DB2, DERBY, ORACLE, and SQLSERVER.

The detect_expression can be used to exclude certain column names from being used. In order to exclude column1 and column2, the expression would be: excluded_column_names=column1,column2

USE_TIMESTAMP

Indicates that the primary key plus a timestamp column (as configured in detect_expression ) will indicate whether a conflict has occurred. If the target timestamp column is not equal to the old source timestamp column, then a conflict has been detected. If a row already exists during an insert then a conflict has been detected.

USE_VERSION

Indicates that the primary key plus a version column (as configured in detect_expression ) will indicate whether a conflict has occurred. If the target version column is not equal to the old source version column, then a conflict has been detected. If a row already exists during an insert then a conflict has been detected.

Important

Be aware that conflict detection will not detect changes to binary columns in the case where use_stream_lobs is true in the trigger for the table. In addition, some databases do not allow comparisons of binary columns whether use_stream_lobs is true or not.

The choice of how to resolve a detected conflict is configured via the resolve_type column. Depending on the setting, two additional boolean settings may also be configured, namely resolve_row_only and resolve_changes_only, as discussed in the resolution settings below.

FALLBACK

Indicates that when a conflict is detected the system should automatically apply the changes anyways. If the source operation was an insert, then an update will be attempted. If the source operation was an update and the row does not exist, then an insert will be attempted. If the source operation was a delete and the row does not exist, then the delete will be ignored. The resolve_changes_only flag controls whether all columns will be updated or only columns that have changed will be updated during a fallback operation.

IGNORE

Indicates that when a conflict is detected the system should automatically ignore the incoming change. The resolve_row_only column controls whether the entire batch should be ignore or just the row in conflict.

MANUAL

Indicates that when a conflict is detected the batch will remain in error until manual intervention occurs. A row in error is inserted into the INCOMING_ERROR table. The conflict detection id that detected the conflict is recorded (i.e., the conflict_id value from CONFLICT), along with the old data, new data, and the "current data" (by current data, we mean the unexpected data at the target which doesn't match the old data as expected) in columns old_data, new_data, and cur_data. In order to resolve, the resolve_data column can be manually filled out which will be used on the next load attempt instead of the original source data. The resolve_ignore flag can also be used to indicate that the row should be ignored on the next load attempt.

NEWER_WINS

Indicates that when a conflict is detected by USE_TIMESTAMP or USE_VERSION that the either the source or the target will win based on the which side has the newer timestamp or higher version number. The resolve_row_only column controls whether the entire batch should be ignore or just the row in conflict.

For each configured conflict, you also have the ability to control if and how much "resolved" data is sent back to the node who's data change is in conflict. This "ping back" behavior is specified by the setting of the ping_back column and can be one of the following values:

OFF

No data is sent back to the originating node, even if the resolved data doesn't match the data the node sent.

SINGLE_ROW

The resolved data of the single row in the batch that caused the conflict is sent back to the originating node.

REMAINING_ROWS.

The resolved data of the single row in the batch in conflict, along with the entire remainder of the batch, is sent back to the originating node.

4.11. File Synchronization

4.11.1. Overview

SymmetricDS not only supports the synchronization of database tables, but it also supports the synchronization of files and folders from one node to another.

File synchronization features include:

  • Monitoring one or more file system directory locations for file and folder changes
  • Support synchronizing a different target directory than the source directory
  • Use of wild card expressions to “include” or “exclude” files
  • Choice of whether to recurse into subfolders of monitored directories
  • Use of existing SymmetricDS routers to subset target nodes based on file and directory metadata
  • Ability to specify if files will be synchronized on creation, or deletion, and/or modification
  • Ability to specify the frequency with which file systems are monitored for changes
  • Ability to extend file synchronization through scripts that run before or after a file is copied to its source location
  • Support for bidirectional file synchronization

Like database synchronization, file synchronization is configured in a series of database tables. The configuration was designed to be similar to database synchronization in order to maintain consistency and to give database synchronization users a sense of familiarity.

For database synchronization, SymmetricDS uses TRIGGER to configure which tables will capture data for synchronization and ROUTER to designate which nodes will be the source of data changes and which nodes will receive the data changes. TRIGGER_ROUTER links triggers to routers.

Likewise, for file synchronization, SymmetricDS uses FILE_TRIGGER to designate which base directories will be monitored. Each entry in FILE_TRIGGER designates one base directory to monitor for changes on the source system. The columns on FILE_TRIGGER provide additional settings for choosing specific files in the base directory that will be monitored, and whether to recurse into subdirectories, etc. File triggers are linked to routers by FILE_TRIGGER_ROUTER. The file trigger router not only links the source and the target node groups, but it also optionally provides the ability to override the base directory name at the target. FILE_TRIGGER_ROUTER also provides a flag that indicates if the target node should be seeded with the files from the source node during SymmetricDS's initial load process.

4.11.2. Operation

Not only is file synchronization configured similar to database synchronization, but it also operates in a very similar way. The file system is monitored for changes via a background job that tracks the file system changes (this parallels the use of triggers to monitor for changes when synchronizing database changes). When a change is detected it is written to the FILE_SNAPSHOT table. The file snapshot table represents the most recent known state of the monitored files. The file snapshot table has a SymmetricDS database trigger automatically installed on it so that when it is updated the changes are captured by SymmetricDS on an internal channel named filesync.

The changes to FILE_SNAPSHOT are then routed and batched by a file-synchronization-specific router that delegates to the configured router based on the FILE_TRIGGER_ROUTER configuration. The file sync router can make routing decisions based on the column data of the snapshot table, columns which contain attributes of the file like the name, path, size, and last modified time. Both old and new file snapshot data are also available. The router can, for example, parse the path or name of the file and use it as the node id to route to.

Batches of file snapshot changes are stored on the filesync channel in OUTGOING_BATCH. The existing SymmetricDS pull and push jobs ignore the filesync channel. Instead, they are processed by file-synchronization-specific push and pull jobs.

When transferring data, the file sync push and pull jobs build a zip file dynamically based on the batched snapshot data. The zip file contains a directory per batch. The directory name is the batch_id. A sync.bsh Bean Shell script is generated and placed in the root of each batch directory. The Bean Shell script contains the commands to copy or delete files at their file destination from an extracted zip in the staging directory on the target node. The zip file is downloaded in the case of a pull, or, in the case of a push, is uploaded as an HTTP multi-part attachment. Outgoing zip files are written and transferred from the outgoing staging directory. Incoming zip files are staged in the filesync_incoming staging directory by source node id. The filesync_incoming/{node_id} staging directory is cleared out before each subsequent delivery of files.

The acknowledgement of a batch happens the same way it is acknowledged in database synchronization. The client responds with an acknowledgement as part of the response during a file push or pull.

4.11.3. File Sync Bean Shell Scripts

There are two types of Bean Shell scripts that can be leveraged to customize file synchronization behavior: before_copy_script and after_copy_script.

Each of these scripts have access to local variables that can be read or set to affect the behavior of copying files.

targetBaseDir

The preset base directory as configured in FILE_TRIGGER or overwritten in FILE_TRIGGER_ROUTER. This variable can be set by the before_copy_script to set a different target directory.

targetFileName

The name of the file that is being synchronized. This variable can be overwritten by the before_copy_script to rename a file at the target.

targetRelativeDir

The name of a directory relative to the target base directory to which the target file will be copied. The default value of this variable is the relative directory of the source. For example, if the source base directory is /src and the target base directory is /tgt and the file /src/subfolder/1.txt is changed, then the default targetRelativeDir will be subfolder. This variable can be overwritten by the before_copy_script to change the relative directory at the target. In the above example, if the variable is set to blank using the following script, then the target file will be copied to /tgt/1.txt.

targetRelativeDir = "";

processFile

This is a variable that is set to true by default. A custom before_copy_script may process the file itself and set this variable to false to indicate that the file should NOT be copied to its target location.

sourceFileName

This is the name of the file.

sourceFilePath

This is the path where the file can be found relative to the batch directory.

batchDir

This is the staging directory where the batch has been extracted. The batchDir + sourceFilePath + sourceFileName can be used to locate the extracted file.

engine

This is the bound instance of the ISymmetricEngine that is processing a file. It gives access to all of the APIs available in SymmetricDS.

sourceNodeId

This is a bound variable that represents the nodeId that is the source of the file.

log

This is the bound instance of an org.slf4j.Logger that can be used to log to the SymmetricDS log file.

4.11.4. File Sync Examples

4.11.4.1. Sync Text Files From Server To Client

The following example is for a configuration with client and server node groups. Creation, modification, and deletion of files with the extension of txt will be captured recursively in the /filesync/server/all directory. A before copy script will set the targetBaseDir to /filesync/clients/{externalId}.

INSERT INTO sym_file_trigger
  (trigger_id,base_dir,recurse,includes_files,excludes_files,sync_on_create,
   sync_on_modified,sync_on_delete,before_copy_script,after_copy_script,
   create_time,last_update_by,last_update_time)
VALUES ('sync_directory','/filesync/server/all',1,'*.txt',null,1,1,1,
  'targetBaseDir = "/filesync/clients/" +
  engine.getParameterService().getExternalId();',null,current_timestamp,'example',
  current_timestamp);

INSERT INTO sym_file_trigger_router
 (trigger_id,router_id,enabled,initial_load_enabled,target_base_dir,
  conflict_strategy,create_time,last_update_by,last_update_time)
VALUES
  ('sync_directory','server_2_client',1,1,'','SOURCE_WINS',current_timestamp,
  'example',current_timestamp);

INSERT INTO sym_router
  (router_id,target_catalog_name,target_schema_name,target_table_name,
  source_node_group_id,target_node_group_id,
  router_type,router_expression,sync_on_update,sync_on_insert,sync_on_delete,
  create_time,last_update_by,last_update_time)
VALUES
  ('server_2_client',null,null,null,'server','client','default',null,1,1,1,
   current_timestamp,'example',current_timestamp);

4.11.4.2. Route changes to a specific node based on a directory name

The following example is also for a configuration with client and server node groups. This example monitors the /filesync/server/nodes directory. It expects the directory to contain subdirectories that are named by the node_ids in the client group. Any files put directly into a folder with the name of the node will be routed to that node.

Note that the router is a Section 4.6.2.2, “Column Match Router” that is matching the client node_id with the value of the RELATIVE_DIR column in FILE_SNAPSHOT. Because the router is looking for an exact match any files in subdirectories would result in a path of node_id/subdir which would not match.


INSERT INTO sym_file_trigger
  (trigger_id,base_dir,recurse,includes_files,excludes_files,sync_on_create,
  sync_on_modified,sync_on_delete,before_copy_script,after_copy_script,create_time,
  last_update_by,last_update_time)
VALUES
  ('node_specific','/filesync/server/nodes',1,null,null,1,1,1,'',null,
  current_timestamp,'example',current_timestamp);

INSERT INTO sym_file_trigger_router
  (trigger_id,router_id,enabled,initial_load_enabled,target_base_dir,
  conflict_strategy,create_time,last_update_by,last_update_time)
VALUES
  ('node_specific','router_files_to_node',1,1,'/filesync/clients','SOURCE_WINS',
  current_timestamp,'example',current_timestamp);

INSERT INTO sym_router
  (router_id,target_catalog_name,target_schema_name,target_table_name,
   source_node_group_id,target_node_group_id,router_type,router_expression,
   sync_on_update,sync_on_insert,sync_on_delete,create_time,last_update_by,
   last_update_time)
VALUES
  ('router_files_to_node',null,null,null,'server','client','column',
  'RELATIVE_DIR = :NODE_ID ',1,1,1,current_timestamp,'example', current_timestamp);

4.12. Jobs

Work done by SymmetricDS is initiated by jobs. Jobs are tasks that are started and scheduled by a job manager. Jobs are enabled by the start.{name}.job property. Most jobs are enabled by default. The frequency at which a job runs in controlled by one of two properties: job.{name}.period.time.ms or job.{name}.cron . If a valid cron property exists in the configuration, then it will be used to schedule the job. Otherwise, the job manager will attempt to use the period.time.ms property.

The frequency of jobs can be configured in either the engines properties file or in PARAMETER . When managed in PARAMETER the frequency properties can be changed in the registration server and when the updated settings sync to the nodes in the system the job manager will restart the jobs at the new frequency settings.

SymmetricDS utilizes Spring's CRON support, which includes seconds as the first parameter. This differs from the typical Unix-based implementation, where the first parameter is usually minutes. For example, */15 * * * * * means every 15 seconds, not every 15 minutes. See Spring's documentation for more details.

Some jobs cannot be run in parallel against a single node. When running on a cluster these jobs use the LOCK table to get an exclusive semaphore to run the job. In order to use this table the cluster.lock.enabled must be set to true.

The three main jobs in SymmetricDS are the route, push and pull jobs. The route job decides what captured data changes should be sent to which nodes. It also decides what captured data changes should be transported and loaded together in a batch. The push and pull jobs are responsible for initiating HTTP communication with linked nodes to push or pull data changes that have been routed.

4.12.1. Route Job

After data is captured in the DATA table, it is routed to specific nodes in batches by the Route Job . It is a single background task that inserts into DATA_EVENT and OUTGOING_BATCH .

The job processes each enabled channel, one at a time, collecting a list of data ids from DATA which have not been routed (see Section 4.12.1.1, “Data Gaps” for much more detail about this step), up to a limit specified by the channel configuration ( max_data_to_route , on CHANNEL ). The data is then batched based on the batch_algorithm defined for the channel and as documented in Section 4.5, “Channel” . Note that, for the default and transactional algorithm, there may actually be more than max_data_to_route included depending on the transaction boundaries. The mapping of data to specific nodes, organized into batches, is then recorded in OUTGOING_BATCH with a status of "RT" in each case (representing the fact that the Route Job is still running). Once the routing algorithms and batching are completed, the batches are organized with their corresponding data ids and saved in DATA_EVENT . Once DATA_EVENT is updated, the rows in OUTGOING_BATCH are updated to a status of New "NE".

The route job will respect the max_batch_size on OUTGOING_BATCH . If the max batch size is reached before the end of a database tranaction and the batch algorithm is set to something other than nontransactional the batch may exceed the specified max size.

The route job delegates to a router defined by the router_type and configured by the router_expression in the ROUTER table. Each router that has a source_node_group_id that matches the current node's source node group id and is linked to the TRIGGER that captured the data gets an opportunity to choose a list of nodes the data should be sent to. Data can only be routed to nodes that belong to the router's target_node_group_id .

4.12.1.1. Data Gaps

On the surface, the first Route Job step of collecting unrouted data ids seems simple: assign sequential data ids for each data row as it's inserted and keep track of which data id was last routed and start from there. The difficulty arises, however, due to the fact that there can be multiple transactions inserting into DATA simultaneously. As such, a given section of rows in the DATA table may actually contain "gaps" in the data ids when the Route Job is executing. Most of these gaps are only temporarily and fill in at some point after routing and need to be picked up with the next run of the Route Job. Thus, the Route Job needs to remember to route the filled-in gaps. Worse yet, some of these gaps are actually permanent and result from a transaction that is rolled back for some reason. In this case, the Route Job must continue to watch for the gap to fill in and, at some point, eventually gives up and assumes the gap is permanent and can be skipped. All of this must be done in some fashion that guarantees that gaps are routed when they fill in while also keeping routing as efficient as possible.

SymmetricDS handles the issue of data gaps by making use of a table, DATA_GAP , to record gaps found in the data ids. In fact, this table completely defines the entire range of data tha can be routed at any point in time. For a brand new instance of SymmetricDS, this table is empty and SymmetricDS creates a gap starting from data id of zero and ending with a very large number (defined by routing.largest.gap.size ). At the start of a Route Job, the list of valid gaps (gaps with status of 'GP') is collected, and each gap is evaluated in turn. If a gap is sufficiently old (as defined by routing.stale.dataid.gap.time.ms , the gap is marked as skipped (status of 'SK') and will no longer be evaluated in future Route Jobs (note that the 'last' gap (the one with the highest starting data id) is never skipped). If not skipped, then DATA_EVENT is searched for data ids present in the gap. If one or more data ids is found in DATA_EVENT , then the current gap is marked with a status of OK, and new gap(s) are created to represent the data ids still missing in the gap's range. This process is done for all gaps. If the very last gap contained data, a new gap starting from the highest data id and ending at (highest data id + routing.largest.gap.size ) is then created. This process has resulted in an updated list of gaps which may contain new data to be routed.

4.12.2. Push and Pull Jobs for Database changes

After database-change data is routed, it awaits transport to the target nodes. Transport can occur when a client node is configured to pull data or when the host node is configured to push data. These events are controlled by the push and the pull jobs . When the start.pull.job SymmetricDS property is set to true , the frequency that data is pulled is controlled by the job.pull.period.time.ms . When the start.push.job SymmetricDS property is set to true , the frequency that data is pushed is controlled by the job.push.period.time.ms .

Data is extracted by channel from the source database's DATA table at an interval controlled by the extract_period_millis column on the CHANNEL table. The last_extract_time is always recorded, by channel, on the NODE_CHANNEL_CTL table for the host node's id. When the Pull and Push Job run, if the extract period has not passed according to the last extract time, then the channel will be skipped for this run. If the extract_period_millis is set to zero, data extraction will happen every time the jobs run.

The maximum number of batches to extract per synchronization is controlled by max_batch_to_send on the CHANNEL table. There is also a setting that controls the max number of bytes to send in one synchronization. If SymmetricDS has extracted the more than the number of bytes configured by the transport.max.bytes.to.sync parameter, then it will finish extracting the current batch and finish synchronization so the client has a chance to process and acknowlege the "big" batch. This may happen before the configured max number of batches has been reached.

Both the push and pull jobs can be configured to push and pull multiple nodes in parallel. In order to take advantage of this the pull.thread.per.server.count or push.thread.per.server.count should be adjusted (from their default value of 10) to the number to the number of concurrent push/pulls you want to occur per period on each SymmetricDS instance. Push and pull activity is recorded in the NODE_COMMUNICATION table. This table is also used to lock push and pull activity across multiple servers in a cluster.

SymmetricDS also provides the ability to configure windows of time when synchronization is allowed. This is done using the NODE_GROUP_CHANNEL_WND table. A list of allowed time windows can be specified for a node group and a channel. If one or more windows exist, then data will only be extracted and transported if the time of day falls within the window of time specified. The configured times are always for the target node's local time. If the start_time is greater than the end_time , then the window crosses over to the next day.

All data loading may be disabled by setting the dataloader.enable property to false. This has the effect of not allowing incoming synchronizations, while allowing outgoing synchronizations. All data extractions may be disabled by setting the dataextractor.enable property to false. These properties can be controlled by inserting into the root server's PARAMETER table. These properties affect every channel with the exception of the 'config' channel.

Node communication over HTTP is represented in the following figure.

Node Communication

Figure 4.1. Node Communication


4.12.3. File Sync Push and Pull Jobs

The File Sync Push and Pull jobs (introduced in version 3.5) are responsible for synchronizing file changes. These jobs work with batches on the filesync channel and create ZIP files of changed files to be sent and applied on other nodes. The parameters job.file.sync.push.period.time.ms and job.file.sync.pull.period.time.ms control how often the jobs runs, which default to every 60 seconds. See also Section 4.12, “Jobs” and Section 4.11.2, “Operation”.

4.12.4. File System Tracker Job

The File System Tracker job (introduced in version 3.5) is responsible for monitoring and recording the events of files being created, modified, or deleted. It records the current state of files to the FILE_SNAPSHOT table. The parameter job.file.sync.tracker.cron controls how often the job runs, which defaults to every 5 minutes. See also Section 4.12, “Jobs” and Section 4.11, “File Synchronization”.

4.12.5. Sync Triggers Job

SymmetricDS examines the current configuration, corresponding database triggers, and the underlying tables to determine if database triggers need created or updated. The change activity is recorded on the TRIGGER_HIST table with a reason for the change. The following reasons for a change are possible:

  • N - New trigger that has not been created before

  • S - Schema changes in the table were detected

  • C - Configuration changes in Trigger

  • T - Trigger was missing

A configuration entry in Trigger without any history in Trigger Hist results in a new trigger being created (N). The Trigger Hist stores a hash of the underlying table, so any alteration to the table causes the trigger to be rebuilt (S). When the last_update_time is changed on the Trigger entry, the configuration change causes the trigger to be rebuilt (C). If an entry in Trigger Hist is missing the corresponding database trigger, the trigger is created (T).

The process of examining triggers and rebuilding them is automatically run during startup and each night by the SyncTriggersJob. The user can also manually run the process at any time by invoking the syncTriggers() method over JMX.

4.12.6. Purge Jobs

Purging is the act of cleaning up captured data that is no longer needed in SymmetricDS's runtime tables. Data is purged through delete statements by the Purge Job . Only data that has been successfully synchronized will be purged. Purged tables include:

The purge job is enabled by the start.purge.job SymmetricDS property. The timing of the three purge jobs (incoming, outgoing, and data gaps) is controlled by a cron expression as specified by the following properties: job.purge.outgoing.cron , job.purge.incoming.cron , and job.purge.datagaps.cron . The default is 0 0 0 * * * , or once per day at midnight.

Two retention period properties indicate how much history SymmetricDS will retain before purging. The purge.retention.minutes property indicates the period of history to keep for synchronization tables. The default value is 5 days. The statistic.retention.minutes property indicates the period of history to keep for statistics. The default value is also 5 days.

The purge properties should be adjusted according to how much data is flowing through the system and the amount of storage space the database has. For an initial deployment it is recommended that the purge properties be kept at the defaults, since it is often helpful to be able to look at the captured data in order to triage problems and profile the synchronization patterns. When scaling up to more nodes, it is recomended that the purge parameters be scaled back to 24 hours or less.