PDB

PulseDB is a database-mapping software library written in Java, it provides a transparent access and manipulation to a great variety of database implementations. PDB provides a DSL that covers most of SQL functionalities and allows to easily integrate persistence into your projects and modules.

Using PDB

Add the following dependency to your Maven pom (example for PDB v2.8.14):

<dependencies>
    ...
	<dependency>
		<groupId>com.feedzai</groupId>
		<artifactId>pdb</artifactId>
		<version>2.8.14</version>
	</dependency>
	...
</dependencies>

Breaking changes

The timeout properties have been redefined in PdbProperties as numeric instead of strings since v2.4.6 - avoid using versions 2.4.4 and 2.4.5.

DatabaseEngine interface has a new method #dropView() since v2.5.3. This method was created without a default so this led to a breaking change. Use 2.5.5 and avoid using 2.5.3 and 2.5.4.

DatabaseEngine methods #getPSResultSet(final String name), #getPSIterator(final String name), #getPSIterator (final String name, final int fetchSize), since 2.7.0, throw an extra ConnectionResetException when the database connection is lost and recovered.

Changes from 2.0.0

It is now possible to call built-in database vendor functions [e.g. f("lower", column("COL1"))]
Added lower and upper functions
Fixed several connection leaks
Fixed MySQL large result fetching

Changes from 2.8.0

It now uses Guava 25.1-jre version, which might require the client to also upgrade it to match the same version

Changes from 2.8.10

H2 version upgraded to 2.1.210
H2Engine is now deprecated and uses the H2v2 legacy mode if this engine is used with the H2v2 driver (for more information regarding the legacy mode see: http://www.h2database.com/html/features.html)
The H2V2Engine was created and it is the engine that should be used from now on (it works on regular mode, not legacy)

Changes from 2.8.14

Added a multithreaded implementation for batches, that uses multiple connections to the database. This may improve write performance to the database, if it is not otherwise limited by resource usage.
Batch implementations should now be obtained by calling the method DatabaseEngine#createBatch(BatchConfig), where the type of config dictates the type of batch implementation that is created.
NOTE: versions 2.8.12 and 2.8.13 already had introduced this, but due to a bug, creating a batch would change the DatabaseEngine, possibly causing it to malfunction. If using that version, avoid the new method to create batches.

Changes from 2.8.16

Version 2.8.15 added back compatibility with Guice v4, but also changed the method SqlBuilder.k to return K instead of Expression. This breaks compatibility with existing code compiled with older PDB versions, so 2.8.16 reverts this change.

Compiling PDB

In order to compile PDB you will need to have the Oracle Driver JAR in your local repository.
The current version assumes Oracle Driver version 12.2.0.1 (even when compiled with this version it is possible to use version 11 drivers in runtime; it is also possible to compile with version 11 instead, but the oracle pom dependency has to be modified).
Please download the driver from the respective Oracle driver page and run the following to install the driver in your local maven repository.

mvn install:install-file -DgroupId=com.oracle.jdbc -DartifactId=ojdbc8 \
-Dversion=12.2.0.1 -Dpackaging=jar -Dfile=ojdbc8.jar

Alternatively you can setup the username/password for accessing Oracle's Maven repository in your settings.xml file.

Running PDB tests

To test PDB with different database engines there are several Maven profiles that can be used, one for each vendor (check list of supported vendors below, under Establishing a connection).

Run the following to run the tests for the chosen vendor specified in lowercase:

mvn test -P<vendor>

NOTE: there is also a "special" profile for H2 to test that engine in server mode (instead of the default H2 embedded); for that case the profile h2remote is used in the <vendor> placeholder.

This will start a docker container running the chosen vendor's database server, and run the tests. The container will be stopped at the end if all tests pass, otherwise will be kept running.

Note: the containers will be started assuming the respective vendor's license agreements have been read and accepted. More info:
Microsoft SQL Server: https://hub.docker.com/r/microsoft/mssql-server-linux/
IBM DB2: https://hub.docker.com/r/ibmcom/db2express-c/

Getting started

Example Description

We describe a scenario where there are some data Providers that share Streams of data with the world. These Streams have a data Type, and they are consumed by some Modules. The entities and its relations are modeled into SQL using PDB in the following sections.

Establishing a connection

With PDB you connect to the database of your preference using the following code.

import static com.feedzai.commons.sql.abstraction.engine.configuration.PdbProperties.*;

(...)

Properties properties = new Properties() {
	{
		setProperty(JDBC, "<JDBC-CONNECTION-STRING>");
		setProperty(USERNAME, "username");
		setProperty(PASSWORD, "password");
		setProperty(ENGINE, "<PDB-ENGINE>");
		setProperty(SCHEMA_POLICY, "create");
	}
};

DatabaseEngine engine = DatabaseFactory.getConnection(properties);

The following table shows how to connect for the supported database vendors.

Vendor	Engine	JDBC
DB2	com.feedzai.commons.sql.abstraction.engine.impl.DB2Engine	jdbc:db2://<HOST>:<PORT>/<DATABASE>
Oracle	com.feedzai.commons.sql.abstraction.engine.impl.OracleEngine	jdbc:oracle:thin:@<HOST>:1521:<DATABASE>
PostgreSQL	com.feedzai.commons.sql.abstraction.engine.impl.PostgreSqlEngine	jdbc:postgresql://<HOST>/<DATABASE>
MySQL	com.feedzai.commons.sql.abstraction.engine.impl.MySqlEngine	jdbc:mysql://<HOST>/<DATABASE>
H2	com.feedzai.commons.sql.abstraction.engine.impl.H2Engine	jdbc:h2:<FILE> \| jdbc:h2:mem
SQLServer	com.feedzai.commons.sql.abstraction.engine.impl.SqlServerEngine	jdbc:sqlserver://<HOST>;database=<DATABASE>

It is also important to select a schema policy. There are four possible schema policies:

create - New entities are created normally.
create-drop - Same as create policy but before the connection is closed all entries created during this session will be dropped.
drop-create - New entities are dropped before creation if they already exist.
none - The program is not allowed to create new entities.

PDB Pool Usage

PDB natively supports connection pools. You can create one using either a Properties or a Map<String, String> instance when defining the properties.

final DatabaseEnginePool dbPool = DatabaseEnginePool.getConnectionPool(properties);

Additionally, you can specify a modifier for the DatabaseEngine. This can be useful when you need to load entities to be able to insert entries on them.

final DatabaseEnginePool dbPool = DatabaseEnginePool.getConnectionPool(properties, engine -> engine.loadEntity(entity));

DatabaseEnginePool implements AutoClosable so you can close the pool when you need, for instance, before exiting the application.

Apart from the already described PDB configurations, you can configure your pool using the parameters in the following table.

The pool.generic.maxTotal, pool.generic.maxIdle, pool.generic.minIdle, and pool.generic.maxWaitMillis are the most common ones.

Property	Description	Default value
`pool.generic.maxTotal`	The maximum number of active `DatabaseEngine` instances that can be allocated from the pool at the same time, or negative for no limit.	8
`pool.generic.maxIdle`	The maximum number of `DatabaseEngine` instances that can remain idle in the pool, without extra ones being released, or negative for no limit.	8
`pool.generic.minIdle`	The minimum number of `DatabaseEngine` instances that can remain idle in the pool, without extra ones being created, or zero to create none.	0
`pool.generic.maxWaitMillis`	The maximum number of milliseconds that the pool will wait (when there are no available `DatabaseEngine` instances) for a `DatabaseEngine` instance to be returned before throwing an error, or -1 to wait indefinitely.	-1
`pool.generic.testOnCreate`	The indication of whether `DatabaseEngine` instances will be validated after creation. If the instance is invalid, the borrow attempt that triggered the `DatabaseEngine` instance creation will fail.	false
`pool.generic.testOnBorrow`	The indication of whether `DatabaseEngine` instances will be validated before being borrowed from the pool. If the instance is invalid, it is dropped from the pool and another one is tried to be borrowed.	true
`pool.generic.testOnReturn`	The indication of whether `DatabaseEngine` instances will be validated before being returned to the pool.	false
`pool.generic.testWhileIdle`	The indication of whether `DatabaseEngine` instances will be validated by the idle evictor (if any). If an instance is invalid, it will be dropped from the pool.	false
`pool.generic.timeBetweenEvictionRunsMillis`	The number of milliseconds to sleep between runs of the idle evictor thread. When non-positive, no idle evictor thread will be run.	-1
`pool.generic.numTestsPerEvictionRun`	The number of `DatabaseEngine` instances to examine during each run of the idle evictor thread (if any).	3
`pool.generic.minEvictableIdleTimeMillis`	The minimum amount of time a `DatabaseEngine` instance may sit idle in the pool before it is eligible for eviction by the idle evictor (if any).	1000 * 60 * 30
`pool.generic.lifo`	True means that the pool returns the most recently used ("last in") `DatabaseEngine` instance in the pool (if there are idle instances available). False means that the pool behaves as a FIFO queue - instances are taken from the idle instance pool in the order that they are returned to the pool.	true
`pool.abandoned.removeAbandonedOnMaintenance` `pool.abandoned.removeAbandonedOnBorrow`	Flags to remove abandoned `DatabaseEngine` instances if they exceed `pool.abandoned.removeAbandonedTimout`. A `DatabaseEngine` instance is considered abandoned and eligible for removal if it has not been used for longer than `pool.abandoned.removeAbandonedTimeout`. Setting `pool.abandoned.removeAbandonedOnMaintenance` to true removes abandoned `DatabaseEngine` instances on the maintenance cycle (when eviction ends). This property has no effect unless maintenance is enabled by setting `pool.generic.timeBetweenEvictionRunsMillis` to a positive value. If `pool.abandoned.removeAbandonedOnBorrow` is true, abandoned `DatabaseEngine` instances are removed each time a instance is borrowed from the pool, with the additional requirements that `[number of active instances]` > `pool.generic.maxTotal` - 3 and `[number of idle instances]` < 2	false
`pool.abandoned.removeAbandonedTimeout`	Timeout in seconds before an abandoned `DatabaseEngine` instance can be removed.	300
`pool.abandoned.logAbandoned`	Flag to log stack traces for application code which abandoned a `DatabaseEngine` instance.	false

If no pool.abandoned property is defined in the configuration file, then no policy to remove abandoned DatabaseEngine instances is applied.

Create Table

We start by creating the table to store the different data Types:

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

DbEntity data_type_table =
	dbEntity()
		.name("data_type")
		.addColumn("id", INT, UNIQUE, NOT_NULL)
		.addColumn("code", STRING, UNIQUE, NOT_NULL)
		.addColumn("description", CLOB)
		.pkFields("id")
		.build();

A table is represented with a DbEntity and its properties can be defined with methods:

Function	Description
name	Select the name for this table.
addColumn	Create a column with a given name and type. Additionally you can had autoincrement behaviour and define some extra constraints. There are two possible constraints available: UNIQUE and NOT_NULL.
pkFields	Define which columns are part of the primary key.

To create the data_type_table you call addEntity method on the previously created database engine. Depending on the policy you chose existing tables might be dropped before creation.

engine.addEntity(data_type_table);

Let's now create the Providers and Streams tables:

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

DbEntity provider_table =
	dbEntity()
		.name("provider")
			.addColumn("id", INT, true, UNIQUE, NOT_NULL)
			.addColumn("uri", STRING, UNIQUE, NOT_NULL)
			.addColumn("certified", BOOLEAN, NOT_NULL)
			.addColumn("description", CLOB)
			.pkFields("id")
			.build();

engine.addEntity(provider_table);

DbEntity stream_table =
	dbEntity()
	.name("stream")
		.addColumn("id", INT, true, UNIQUE, NOT_NULL)
		.addColumn("provider_id", INT, NOT_NULL)
		.addColumn("data_type_id", INT, NOT_NULL)
		.addColumn("description", CLOB)
		.pkFields("id")
		.addFk(
			dbFk()
				.addColumn("provider_id")
				.foreignTable("provider")
				.addForeignColumn("id"),
			dbFk()
				.addColumn("data_type_id")
				.foreignTable("data_type")
				.addForeignColumn("id"))
		.addIndex(false, "provider_id", "data_type_id")
		.build();

engine.addEntity(stream_table);

You may have noticed that this stream_table has some foreign keys, which we define using the addFK method. This method receives a list of the foreign keys constraints. A foreign key is created with dbFk(), and it is defined using these methods:

Function	Description
addColumn	Define which columns will be part of this constraint.
foreignTable	Define the foreign table we are referring to.
addForeignColumn	Selects the affected columns in the foreign table.

Wait! Looks like we also created an index in the Stream table.

Function	Description
addIndex	Creates and index for the listed columns. If not specified, an index is not unique.

The rest of the example case is created with the following code:

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

DbEntity module_table =
	dbEntity()
		.name("module")
        .addColumn("name", STRING, UNIQUE, NOT_NULL)
        .build();

engine.addEntity(module_table);

DbEntity stream_to_module_table =
	dbEntity()
		.name("stream_to_module")
			.addColumn("name", STRING, NOT_NULL)
			.addColumn("stream_id", INT, NOT_NULL)
			.addColumn("active", INT)
			.pkFields("name", "stream_id")
			.addFk(
				dbFk()
					.addColumn("name")
					.foreignTable("module")
					.addForeignColumn("name"),
				dbFk()
					.addColumn("stream_id")
					.foreignTable("stream")
					.addForeignColumn("id"))
            .build();

engine.addEntity(stream_to_module_table);

Drop Table

When you are done with this example you might want to clean the database.

engine.dropEntity("stream_to_module");

Function	Description
dropEntity	Drops an entity given the name.

Alter Table

With PDB you can change some aspects of a previously created tables. After calling the the addEntity method with the created entity you can continue to modify this local representation by calling the methods described in the previous sections. Then to synchronize the local representation with the actual table in the database you call the updateEntity method.

data_type_table = data_type_table
                    .newBuilder()
                    .removeColumn("description")
                    .build();

engine.updateEntity(data_type_table);

Function	Description
removeColumn	Removes a column from the local representation of the table.
updateEntity	Synchronizes the entity representation with the table in the database. If schema policy is set to drop-create the whole table is dropped and created again.

Another mechanism to alter table is by using the AlterColumn expression creation and the executeUpdate method provided by the database engine. In this case changes are made to each column, one at a time.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

Expression alterColumn = alterColumn(
                            table("stream_to_module"),
					        dbColumn("active", BOOLEAN).addConstraint(NOT_NULL).build());

engine.executeUpdate(alterColumn);

Function	Description
alterColumn	Creates a expression of changing a given table schema affecting a column.
dbColumn	Column definition. Provide new type and autoincrement behavior.
addConstraint	Define the constraints you want the column to oblige to.
addConstraints	Define the constraints you want the column to oblige to.

It is also possible to remove the the primary key constraint.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

Expression dropPrimaryKey = dropPK(table("TEST"));

engine.executeUpdate(dropPrimaryKey);

Function	Description
dropPK	Drops the primary key constraint on the given table.

Insertion Queries

Now that we have the structure of the database in place, let's play it with some data. An EntityEntry it's our representation of an entry that we want to add to the database.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

EntityEntry data_type_entry =
	entry()
		.set("id", 1)
		.set("code", "INT16")
		.set("description", "The type of INT you always want!")
		.build();

Function	Description
set	Define the value that will be assigned to a given column.

Notice that the values for each column were defined using the set method. A new entry for the database is persisted with engine's method persist.

engine.persist("data_type", data_type_entry, false);

Function	Description
persist	Select the table in which the new entity will be inserted. If the affected table has an autoincrement column you might want to activate this flag. In case that the autoincrement behaviour is active, this method returns the generated key.

If you want to use the autoincrement behavior you must activate the autoincrement flag when defining the entity.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

EntityEntry provider_entry =
	entry()
		.set("uri", "from.some.where")
		.set("certified", true)
		.build();

long generatedKey = engine.persist("provider", provider_entry, true);

Batches

PDB also provides support for batches. With batches you reduce the amount of communication overhead, thereby improving performance.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

engine.beginTransaction();

try {
    EntityEntry entry = entry()
    	.set("code", "SINT")
    	.set("description", "A special kind of INT")
    	.build();

    engine.addBatch("data_type", entry);

    entry = entry()
    	.set("code", "VARBOOLEAN")
    	.set("description", "A boolean with a variable number of truth values")
    	.build();

    engine.addBatch("data_type", entry);

    // Perform more additions...

    engine.flush();
    engine.commit();
} finally {
    if (engine.isTransactionActive()) {
        engine.rollback();
    }
}

Function	Description
beginTransaction	Starts a transaction.
addBatch	Adds an entry to the current batch.
flush	Executes all entries registered in the batch.
commit	Commits the current transaction transaction.
isTransactionActive	Tests if the transaction is active.
rollback	Rolls back the transaction.

Updating and Deleting Queries

Now you might want to the update data or simply erase them. Let's see how this can be done.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

engine.executeUpdate(
	update(table("stream"))
	.set(
		eq(column("cd"), k("Double")),
		eq(column("description", k("Double precision floating point number")))
	.where(eq(column(id), k(1))));

Expressions that produce changes to the database are executed with engine's executeUpdate method. There are some defined static methods that allow you to create SQL queries. Update is one of them. In this section we describe queries that make changes to the database, while in the following section selection queries will be present in detail.

Function	Description
update	Creates an update query that will affect the table referred by the given expression.
set	Expression that defines the values that will be assigned to each given column.
where	Expression for filtering/selecting the affected entries.
table	Creates a reference to a table of your choice.

Maybe you want to delete entries instead. In that case creating a delete query is required.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

engine.executeUpdate(
	delete(table("stream")));

engine.executeUpdate(
	delete(table("stream"
		.where(eq(column(id), k(1))));

Function	Description
delete	Creates a delete query that will affect the table referred by the given expression.
where	Expression for filtering/selecting the affected entries.

Truncate Queries

If what you seek is to delete all table entries at once, it is recommended to use the truncate query.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

engine.executeUpdate(truncate(table("stream")));

Function	Description
truncate	Creates a truncate query that will affect the table referred by the given expression.

Selection Queries

Now things will get interesting. In this section we will see how PDB uses SQL to select data from the database. Using the query method we get the result for any given query as a list of entries. These entries are represented as a map of column name to content.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

Expression query =
	select(all())
	.from(table("streams"));

// Fetches everything! Use with care when you know the result set is small.
List<Map<String, ResultColumn>> results = engine.query(query);

for(Map<String, ResultColumn> result : results) {
    Int id = result.get("id").toInt();
    String description = result.get("description").toString();
	System.out.println(id + ": "+ description);
}

// If your result set is large consider using the iterator.
ResultIterator it = engine.iterator(select(all()).from(table("streams")));
Map<String, ResultColumn> next;
while ((next = it.next()) != null) {
    Int id = next.get("id").toInt();
    String description = next.get("description").toString();
	System.out.println(id + ": "+ description);
}

The iterator closes automatically when it reaches the end of the result set, but you can close it on any time by calling it.close().

Function	Description
query	Processes a given query and computes the corresponding result. It returns a List of results if any. For each column a result is a Map that maps column names to ResultColumn objects.
iterator	Returns an iterator to cycle through the result set. Preferable when dealing with large result sets.
toXXX	ResultColumn provides methods to convert the data to the type of your preference. It throws an exception if you try to convert the underlying data to some incompatible type.

Let's see this simple query in more detail. Where we list all entries in table Streams and return all columns.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(all())
	.from(table("streams")));

Function	Description
select	Expression defining the selection of columns or other manipulations of its values.
distinct	Filter the query so it only returns distinct values.
from	Defines what tables or combination of them the data must be fetched from. By default the listed sources will be joined together with an inner join.
all	Defines a reference to all column the underlying query might return.
k	Creates a Constant from obj.
lit	Creates a Literal from obj.
column	Defines a reference to a given column.
with	Provides a way to write auxiliary statements for use in a larger query.

This is useful but not very interesting. We should proceed by filtering the results with some condition of our choice.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(all())
	.from(table("streams"))
	.where(eq(column("data_type_id"), k(4)))
	.andWhere(like(column("description"), k("match t%xt"))));

Function	Description
where	Defines a series of testes a entry must oblige in order to be part of the result set.
andWhere	If there is already ab where clause it defines an and expression with the old clause.
eq	Applies the equality condition to the expressions. It is also used in insertion queries to represent attribution.
neq	Negation of the equality condition.
like	Likelihood comparison between expression. Those expression must resolve to String constants or columns of the same type.
lt	Predicate over numerical or alphanumerical values.
lteq	Predicate over numerical or alphanumerical values.
gt	Predicate over numerical or alphanumerical values.
gteq	Predicate over numerical or alphanumerical values.

A more complex filter would be one that select Streams from a given range of data Types and a set of Providers. And we manage just that with the following query.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(all())
	.from(table("streams"))
	.where(
		and(between(column("data_type_id"), k(2), k(5)),
			notIn(column("provider_id"), L(k(1), k(7), k(42))))));

Function	Description
and	Computes the boolean result of the underlying expressions.
or	Computes the boolean result of the underlying expressions.
between	Defines a test condition that asserts if exp1 is part of the range of values from exp2 to exp3.
notBetween	Defines a test condition that asserts if exp1 is part of the range of values from exp2 to exp3.
in	Defines a test condition that asserts if exp1 is part of exp2. Expression exp2 might be a List of constants or the result of a sub query.
notIn	Defines a test condition that asserts if exp1 is part of exp2. Expression exp2 might be a List of constants or the result of a sub query.
L	Defines a list of elements represent by the passing expressions.
caseWhen	Defines a test using a list of conditions by going through them and returning a value when the first condition is met. If none are met, it will return the otherwise clause or NULL if not defined.
cast	Specifies how to perform a conversion between two data types.

It is widely known that greater the id greater the Stream of data. For this purpose you just design a query that selects the maximum Stream id of data Type 4 from Provider 1. You might just get a raise for this.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(max(column("id")).alias("the_best"))
	.from(table("streams"))
	.where(
		and(eq(column("data_type_id"), k(4)),
			eq(column("provider_id"), k(1)))));

Function	Description
alias	Assigns an alias to the expression.
count	Aggregation operator for numeric values. They are applicable to expression involving columns.
max	Aggregation operator for numeric values. They are applicable to expression involving columns.
min	Aggregation operator for numeric values. They are applicable to expression involving columns.
sum	Aggregation operator for numeric values. They are applicable to expression involving columns.
avg	Aggregation operator for numeric values. They are applicable to expression involving columns.
stddev	Aggregation operator for numeric values. They are applicable to expression involving columns.
stringAgg	Aggregation operator that aggregates data of a column into a string.
[concat](https://feedzai.github.io/pdb/com/feedzai/commons/sql/abstraction/dml/dialect/SqlBuilder.html#concat(com.feedzai.commons.sql.abstraction.dml.Expression, com.feedzai.commons.sql.abstraction.dml.Expression...))	Concatenates the expressions with a delimiter.
floor	Operator that returns the largest integer value that is smaller than or equal to a number. They are applicable to expression involving columns.
ceil	Operator that returns the smallest integer value that is larger than or equal to a number. They are applicable to expression involving columns.
udf	If you have defined your own sql function you may access it with udf.

Sometimes it is required to merge the content of more than one table. For that purpose you can use joins. They allow you to merge content of two or more table regrading some condition. In this example we provide a little bit more flavor to the result by adding the data Type information to the Stream information.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(all())
	from(table("stream")
		.innerJoin((table("data_type"),
					join(
					    column("stream", "data_type_id"),
					    column("data_type", "id")))));

Function	Description
innerJoin	Merges the table results of two expression regarding a condition.
leftOuterJoin	Merges the table results of two expression regarding a condition.
rightOuterJoin	Merges the table results of two expression regarding a condition.
fullOuterJoin	Merges the table results of two expression regarding a condition.
join	Applies the equality condition to the expressions.
union	Unions the results of multiple expressions.

The market is collapsing! The reason, some say, is that some provider messed up. In your contract it is stated that Provider with id 4 provides a given number of streams for each data_type. With the following query you will find out if the actual data in the database matches the contract. By filtering the results to only account for Provider 4 and grouping on the data Type you are able to count the number of streams by Type. Your Boss will be pleased.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(column("data_type_id"), count(column("id")).alias("count"))
	.from(table("streams"))
	.where(eq(column("provider_id"), k(4)))
	.groupby(column("data_type_id"))
	.orderby(column("data_type_id").asc());

Function	Description
groupby	Groups the result on some of the table columns.
orderby	Orders the result according to some expression of the table columns.
asc	Sets the ordering as ascendant.
desc	Sets the ordering as descendant.

Some documents leaked online last week suggest that there are some hidden message in our data. To visualize this hidden message we need to do some arithmetic's with the ids of the provider and data_type on table Streams. Even more strange is the need to filter the description column, where in case of a null value an alternative is presented.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(
		plus(
			column("data_type_id"),
			column("provider_id"),
			k(1)
		).alias("mess_ids"),
		coalesce(
			column("description"),
			k("Romeo must die")))
	.from(table("streams")));

Function	Description
minus	Applies the subtraction operator to the list of value with left precedence.
mult	Applies the multiplication operator to the list of value with left precedence.
plus	Applies the addiction operator to the list of value with left precedence.
div	Applies the division operator to the list of value with left precedence.
mod	Applies the module operator to the list of value with left precedence.
coalesce	Coalesce tests a given expression and returns its value if it is not null. If the primary expression is null, it will return the first alternative that is not.

For this next example, imagine you want to select all Streams for which the sum of data_type_id and provider_id is greater than 5. It might not be a very useful query, but when you had that you just want 10 rows of the result with and offset of 2, people might wonder what you are up to.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

results = engine.query(
	select(all())
	.from(table("streams"))
	.having(
		gt(plus(
				column("data_type_id"),
				column("provider_id")),
			k(5)))
	.limit(10)
	.offset(2));

Function	Description
having	Query will select only the result rows where aggregate values meet the specified conditions.
limit	Defines the number of rows that the query returns.
offset	Defines the offset for the start position of the resulting rows.

Prepared Statements

PDB also allows the creation of prepared statements. Here you have two of the previous example queries done using prepared statements

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

Query query = select(all())
		.from(table("streams"))
		.where(eq(column("data_type_id"), lit("?")))
		.andWhere(like(column("description"), k("match t%xt")));

engine.createPreparedStatement("MyPS", query);

// It is always a good policy to clear the parameters
engine.clearParameters("MyPS");
engine.setParameter("MyPS", 1, 10);

engine.executePS("MyPS");
List<Map<String, ResultColumn>> result = engine.getPSResultSet("MyPS");

In PDB prepared statements are stored internally and they are maintained if the connection is lost, but the parameters are always lost.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

Update update = update(table("stream"))
			.set(
				eq(column("cd"), lit("?")),
				eq(column("description", lit("?")))
			.where(eq(column(id), k(1))));

engine.createPreparedStatement("MyPS", query);

engine.clearParameters("MyPS");
engine.setParameter("MyPS", 1, "INT");
engine.setParameter("MyPS", 2, "Your regular integer implementation.");

int affectedEntries = engine.executePSUpdate("MyPS");

Function	Description
createPreparedStatement	Creates a prepared statement and assigns it to a given identifier.
clearParameters	Clears the parameters of a given prepared statement.
setParameter	Assigns a object to a given parameter of a prepared statement.
executePS	Executes a given prepared statement.
executePSUpdate	Executes a given update prepared statement and returns the number of affected rows.
getPSResultSet	Returns the result set of the last executed query.
getPSIterator	Returns an iterator to the result set of the last executed query.

Create View

Sometimes, for security reasons or just for simplicity, it is useful to have a view of the database.

import static com.feedzai.commons.sql.abstraction.dml.dialect.SqlBuilder.*;

(...)

Expression view = createView("simple_stream")
					.as(select(column("id"), column("data_type_id"))
						.from(table("stream")))
					.replace();

engine.executeUpdate(view);

Function	Description
createView	Creates a view with the given name.
as	Defines the query that provides the data for this view.
replace	Whether or not the view creation is authorized to overwrite over existing views.

Drop View

After creating a view, you may also want to delete it.

engine.dropView("view_name");

Function	Description
dropView	Drops a view with the given name.

Further Documentation

For more insight on the available functionality please see projects javadoc.

Contact

For more information please contact opensource@feedzai.com, we will happily answer your questions.

Special Thanks

Miguel Miranda (miguelnmiranda@gmail.com) for the documentation and first steps on making this library opensource

License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Name		Name	Last commit message	Last commit date
Latest commit History 561 Commits
.github		.github
.m2		.m2
.mvn		.mvn
src		src
.gitignore		.gitignore
LICENSE		LICENSE
Makefile		Makefile
README.md		README.md
header.txt		header.txt
pom.xml		pom.xml

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Repository files navigation

PDB

Using PDB

Breaking changes

Changes from 2.0.0

Changes from 2.8.0

Changes from 2.8.10

Changes from 2.8.14

Changes from 2.8.16

Compiling PDB

Running PDB tests

Getting started

Index

Example Description

Establishing a connection

PDB Pool Usage

Create Table

Drop Table

Alter Table

Insertion Queries

Batches

Updating and Deleting Queries

Truncate Queries

Selection Queries

Prepared Statements

Create View

Drop View

Further Documentation

Contact

Special Thanks

License

About

Releases

Packages

Contributors 35

Languages

License

feedzai/pdb

Folders and files

Latest commit

History

Repository files navigation

PDB

Using PDB

Breaking changes

Changes from 2.0.0

Changes from 2.8.0

Changes from 2.8.10

Changes from 2.8.14

Changes from 2.8.16

Compiling PDB

Running PDB tests

Getting started

Index

Example Description

Establishing a connection

PDB Pool Usage

Create Table

Drop Table

Alter Table

Insertion Queries

Batches

Updating and Deleting Queries

Truncate Queries

Selection Queries

Prepared Statements

Create View

Drop View

Further Documentation

Contact

Special Thanks

License

About

Resources

License

Stars

Watchers

Forks

Releases

Packages 0

Contributors 35

Languages

Packages