Java Developer Guide - Kinetica Docs

The following guide provides step-by-step instructions to get started writing Java applications using Kinetica. This guide demonstrates only a small set of the available API. A detailed description of the complete interface is available under Java API Reference.

Prerequisites

Data File

The tutorial java file makes reference to a data file in the current directory. This path can be updated to point to a valid path on the host where the file will be located, or the script can be run with the data file in the current directory.

Taxi Data File Path

final String CSV_FILE_PATH = "./taxi_trip_data.csv";

API Download

Maven Download

We suggest using Maven as the build tool for your Java project. To use the Kinetica Java API, ensure the Maven Central repository is reachable and add the Kinetica Java API dependency that matches that of the targeted Kinetica database, as shown below:

API Version

<properties>
	<gpudb-api.version>[7.2.3.9,7.3.0.0-SNAPSHOT)</gpudb-api.version>
</properties>

API Dependency

<dependencies>
	<dependency>
		<groupId>com.gpudb</groupId>
		<artifactId>gpudb-api</artifactId>
		<version>${gpudb-api.version}</version>
		<type>jar</type>
	</dependency>
</dependencies>

The pom.xml file used for the tutorial can be found below.

Manual Download

The source code for the Java API is also available for download from the GitHub repository kineticadb/kinetica-api-java. Follow the instructions in the included README file to build the API library.

File Hierarchy

The tutorial was setup like the below diagram:

java_tutorial/
   ├── java_tutorial.out
   ├── pom.xml
   ├── src/
   │    └── main/
   │         └── java/
   │              └── Tutorial.java
   └── target/
        └── docsite-tutorial-3.0-jar-with-dependencies.jar

Connecting to the Database

To connect to the database, instantiate an object of the GPUdb class, providing the connection URL, username, & password to the database server. For more details on connecting to the database, see Connecting via API.

Connect to the Database

GPUdb.Options options = new GPUdb.Options();
options.setUsername(user);
options.setPassword(pass);
GPUdb kdb = new GPUdb(url, options);

Creating a Schema

All tables & views must be created within a schema. So, the first step will be to create a schema to contain all of the tables & views created within this tutorial.

Create Tutorial Schema

final String SCHEMA_NAME = "tutorial_java";
kdb.createSchema(SCHEMA_NAME, null);

Creating a Type

Before a table can be created and any data can be loaded into it, a type needs to be defined. The type is a class, extended from RecordObject, using annotations to describe which class instance variables are fields (i.e., columns), what type they are, and any special handling they should receive. For this tutorial, three types will be used to create three corresponding tables:

A base table containing a sample of NYC taxi cab ride data
A lookup table containing sample cab vendor information (created in the example below)
A 1-to-1 relation table containing payment information for a subset of the cab-ride transactions

The definition of the type for the vendor table follows:

Define a Type

public static class Vendor extends RecordObject
{
	/* Create column(s), establish its ordering, give it property
	 * sub-type(s), give it a column type, and give it a name. */
	@RecordObject.Column(order = 0, properties = { "char4", "primary_key" })
	public String vendor_id;
	@RecordObject.Column(order = 1, properties = { "char64" })
	public String vendor_name;
	@RecordObject.Column(order = 2, properties = { "char16", "nullable" })
	public String phone;
	@RecordObject.Column(order = 3, properties = { "char64", "nullable" })
	public String email;
	@RecordObject.Column(order = 4, properties = { "char64" })
	public String hq_street;
	@RecordObject.Column(order = 5, properties = { "char8", "dict" })
	public String hq_city;
	@RecordObject.Column(order = 6, properties = { "char2", "dict" })
	public String hq_state;
	@RecordObject.Column(order = 7)
	public Integer hq_zip;
	@RecordObject.Column(order = 8)
	public Integer num_emps;
	@RecordObject.Column(order = 9)
	public Integer num_cabs;

	public Vendor() {}

	/* Create a constructor for the class that will take parameters so that
	 * Bulk Inserting is easier */
	public Vendor(
			String vendor_id, String vendor_name, String phone,
			String email, String hq_street, String hq_city, String hq_state,
			Integer hq_zip, Integer num_emps, Integer num_cabs
	)
	{
		this.vendor_id = vendor_id;
		this.vendor_name = vendor_name;
		this.phone = phone;
		this.email = email;
		this.hq_street = hq_street;
		this.hq_city = hq_city;
		this.hq_state = hq_state;
		this.hq_zip = hq_zip;
		this.num_emps = num_emps;
		this.num_cabs = num_cabs;
	}
}

Although a constructor is not required, if the class does have any constructors, it must have a constructor with no parameters. Other constructors can be added, as necessary

Once defined, the type needs to be created with a call to createType():

Create a Type

String vendorTypeId = RecordObject.createType(Vendor.class, kdb);

Creating a Table

The returned object from the createType() call contains a unique type identifier assigned by the system. This identifier can then be used in the request to create a corresponding table. The examples below outline creating a table with either a single request object (vendor table) or a parameterized call (payment table):

Create a Table (via Request Object)

CreateTableRequest vendorCreateReq = new CreateTableRequest();
vendorCreateReq.setTableName(TABLE_VENDOR);
vendorCreateReq.setTypeId(vendorTypeId);
vendorCreateReq.setOptions(GPUdb.options(CreateTableRequest.Options.IS_REPLICATED, "true"));
kdb.createTable(vendorCreateReq);

Create a Table (via Parameters)

kdb.createTable(TABLE_PAYMENT, paymentTypeId, null);

Inserting Data

Once the table is created, data can be inserted into it. There is a convenience class called BulkInserter, which facilitates inserting records into a table in batches; see Distributed Ingest for details. For this tutorial, only the native Java API call insertRecords() will be used.

Key/Value Record

In this example, values are assigned individually to fields after creating a Payment object with the default constructor.

Assign After Default Constructor

// Create a record object and assign values to properties
Payment paymentDatum = new Payment();
paymentDatum.payment_id = 189;
paymentDatum.payment_type = "No Charge";
paymentDatum.credit_type = null;
paymentDatum.payment_timestamp = null;
paymentDatum.fare_amount = 6.5;
paymentDatum.surcharge = 0;
paymentDatum.mta_tax = 0.6;
paymentDatum.tip_amount = 0;
paymentDatum.tolls_amount = 0;
paymentDatum.total_amount = 7.1;

// Insert the record into the table
int numInserted = kdb.insertRecords(TABLE_PAYMENT, Arrays.asList(paymentDatum), null).getCountInserted();

In-Line Record

In this example, values are passed in to the Vendor object’s parameterized constructor.

Assign by Parameterized Constructor

/* Create a list of in-line records. The order of the values must match
 * the column order in the type */
List<Vendor> vendorRecords = new ArrayList<>();
vendorRecords.add(new Vendor(
		"VTS","Vine Taxi Service","9998880001","admin@vtstaxi.com",
		"26 Summit St.","Flushing","NY",11354,450,400));
vendorRecords.add(new Vendor(
		"YCAB","Yes Cab","7895444321",null,
		"97 Edgemont St.","Brooklyn","NY",11223,445,425));
vendorRecords.add(new Vendor(
		"NYC","New York City Cabs",null,"support@nyc-taxis.com",
		"9669 East Bayport St.","Bronx","NY",10453,505,500));
vendorRecords.add(new Vendor(
		"DDS","Dependable Driver Service",null,null,
		"8554 North Homestead St.","Bronx","NY",10472,200,124));
vendorRecords.add(new Vendor(
		"CMT","Crazy Manhattan Taxi","9778896500","admin@crazymanhattantaxi.com",
		"950 4th Road Suite 78","Brooklyn","NY",11210,500,468));
vendorRecords.add(new Vendor(
		"TNY","Taxi New York",null,null,
		"725 Squaw Creek St.","Bronx","NY",10458,315,305));
vendorRecords.add(new Vendor(
		"NYMT","New York Metro Taxi",null,null,
		"4 East Jennings St.","Brooklyn","NY",11228,166,150));
vendorRecords.add(new Vendor(
		"5BTC","Five Boroughs Taxi Co.","4566541278","mgmt@5btc.com",
		"9128 Lantern Street","Brooklyn","NY",11229,193,175));

// Insert the records into the Vendor table
numInserted = kdb.insertRecords(TABLE_VENDOR, vendorRecords, null).getCountInserted();

CSV

CSV and other data files can be loaded into Kinetica via KiFS using the GPUdbFileHandler. This can upload files into KiFS for later ingestion or stage them temporarily and ingest them all at once.

Insert from File

GPUdbFileHandler fh = new GPUdbFileHandler(kdb);
fh.ingest(Arrays.asList(CSV_FILE_PATH), TABLE_TAXI, null, null);

Retrieving Data

Once the table is populated with data, the data can be retrieved from the system by a call to getRecords(tableName, offset, limit, options) using in-line parameter-passing.

Retrieve Records (via Parameters)

// Retrieve no more than 10 records from payments using in-line request parameters
GetRecordsResponse<Payment> getPaymentRecordsResp = kdb.getRecords(
		TABLE_PAYMENT,
		0,
		10,
		GPUdb.options(GetRecordsRequest.Options.SORT_BY,"payment_id")
);
System.out.println(
		"Payment ID Payment Type Credit Type Payment Timestamp " +
		"Fare Amount Surcharge MTA Tax Tip Amount Tolls Amount Total Amount"
);
System.out.println(
		"========== ============ =========== ================= " +
		"=========== ========= ======= ========== ============ ============"
);
for (Payment p : getPaymentRecordsResp.getData())
	System.out.printf(
			"%10d %-12s %-11s %17s %11.2f %9.2f %7.2f %10.2f %12.2f %12.2f%n",
			p.payment_id, Objects.toString(p.payment_type, ""), Objects.toString(p.credit_type, ""),
			Objects.toString(p.payment_timestamp, ""), p.fare_amount, p.surcharge, p.mta_tax,
			p.tip_amount, p.tolls_amount, p.total_amount
	);

One can also invoke getRecords(request) using the GetRecordsRequest request class. This object contains all the parameters for the method call, and can be reused in successive calls, avoiding re-specifying query parameters.

Retrieve Records (via Request Object)

// Retrieve all records from the Vendor table using a request object
GetRecordsRequest vendorReq = new GetRecordsRequest();
vendorReq.setTableName(TABLE_VENDOR);
vendorReq.setOffset(0);
vendorReq.setLimit(GPUdb.END_OF_SET);
vendorReq.setOptions(GPUdb.options(GetRecordsRequest.Options.SORT_BY, "vendor_id"));
GetRecordsResponse<Vendor> vendorResp = kdb.getRecords(vendorReq);
System.out.println(
		"Vendor ID Vendor Name                Phone       Email                         " +
		"HQ Street                HQ City  HQ State HQ Zip # Employees # Cabs"
);
System.out.println(
		"========= ========================== =========== ============================= " +
		"======================== ======== ======== ====== =========== ======"
);
for (Vendor v : vendorResp.getData())
	System.out.printf(
			"%-9s %-26s %-11s %-29s %-24s %-8s %-8s %-6d %11d %6d%n",
			v.vendor_id, v.vendor_name, Objects.toString(v.phone, ""), Objects.toString(v.email, ""),
			v.hq_street, v.hq_city, v.hq_state, v.hq_zip, v.num_emps, v.num_cabs
	);

For large tables, the data can be easily be retrieved in smaller blocks by using the offset and limit parameters. The returned response also contains the type (column definitions) of the results. Also, note that all query related methods have the above two versions—with the request object and with the parameters passed directly to the method.

Updating Records

Use updateRecords() to update matching key values for any records in a table.

Update Records

// Update the e-mail, number of employees, and number of cabs of the DDS vendor
List<Map<String, String>> newValsList = new ArrayList<>();
Map<String,String> newVals = new HashMap<>();
newVals.put("email", "'management@ddstaxico.com'");
newVals.put("num_emps", "num_emps + 2");
newVals.put("num_cabs", "num_cabs + 1");
newValsList.add(newVals);
kdb.updateRecords(
		TABLE_VENDOR,
		Arrays.asList("vendor_id = 'DDS'"),
		newValsList,
		null,
		GPUdb.options(
				UpdateRecordsRequest.Options.USE_EXPRESSIONS_IN_NEW_VALUES_MAPS,
				UpdateRecordsRequest.Options.TRUE
		)
);

Deleting Records

Use deleteRecords() to delete records from a table. A list can be used to specify which records to delete based on matching expressions. Set DELETE_ALL_RECORDS to TRUE to delete all records in a table.

Delete Records

// Delete payment 189
String delExpr = "payment_id = 189";
kdb.deleteRecords(TABLE_PAYMENT, Arrays.asList(delExpr), null);

Alter Table

Some properties can be altered or added after table creation, using alterTable(), including indexes and dictionary encoding.

Indexes

Using the alterTable() method, you can create indexes on columns using the CREATE_INDEX action paired with a column name.

Index Column

/* Add column indexes on:
 *   - payment table, fare_amount (for query-chaining filter example)
 *   - taxi table, passenger_count (for filter-by-range example) */
kdb.alterTable(TABLE_PAYMENT, AlterTableRequest.Action.CREATE_INDEX, "fare_amount", null);

kdb.alterTable(TABLE_TAXI, AlterTableRequest.Action.CREATE_INDEX, "passenger_count", null);

Dictionary Encoding

Applying dictionary encoding via alterTable() involves adding a new property to a column using the CHANGE_COLUMN action paired with a column name & definition.

Dictionary Encode Column

// Apply dictionary encoding to the payment type column
AlterTableResponse dictEncResp = kdb.alterTable(
		TABLE_TAXI,
		AlterTableRequest.Action.CHANGE_COLUMN,
		columnName,
		GPUdb.options(
				AlterTableRequest.Options.COLUMN_PROPERTIES,
				"char4,dict"
		)
);

To add a new property, all existing column properties must be listed along with any new properties.

Filters

Filters are an easy way to reduce larger tables into more concise views using expressions.

Count Value-Filtered Records

// Filter for only payments with no corresponding payment type, returning the
// count of records found
long f1Count = kdb.filter(TABLE_PAYMENT, VIEW_EXAMPLE1, "IS_NULL(payment_type)", null).getCount();

Count Using Filter Chaining

// Using query chaining, filter null payment type records with a fare amount greater than 8
long f2Count = kdb.filter(VIEW_EXAMPLE1, VIEW_EXAMPLE2, "fare_amount > 8", null).getCount();

Count List-Filtered Records

// Filter by list where vendor ID is either NYC or YCAB
Map<String, List<String>> columnValuesMap = new HashMap<>();
columnValuesMap.put("vendor_id", Arrays.asList("NYC", "YCAB"));
long f3Count = kdb.filterByList(TABLE_TAXI, VIEW_EXAMPLE3, columnValuesMap, null).getCount();

Count Range-Filtered Records

// Filter by range trip with passenger count between 1 and 3
long f4Count = kdb.filterByRange(TABLE_TAXI, VIEW_EXAMPLE4, "passenger_count", 1, 3, null).getCount();

Aggregates

Kinetica supports various aggregate and group-by queries, which group and aggregate your data to return counts and useful statistics.

Calculate Count/Min/Mean/Max

// Aggregate count, min, mean, and max on the trip distance
Map<String,Double> a1Resp = kdb.aggregateStatistics(
		TABLE_TAXI,
		"trip_distance",
		AggregateStatisticsRequest.Stats.COUNT + "," +
		AggregateStatisticsRequest.Stats.MIN + "," +
		AggregateStatisticsRequest.Stats.MAX + "," +
		AggregateStatisticsRequest.Stats.MEAN,
		null
).getStats();
System.out.println("Statistics of values in the trip_distance column:");
System.out.printf(
		"\tCount: %5.0f%n\tMin:   %5.2f%n\tMean:  %5.2f%n\tMax:   %5.2f%n%n",
		a1Resp.get(AggregateStatisticsRequest.Stats.COUNT),
		a1Resp.get(AggregateStatisticsRequest.Stats.MIN),
		a1Resp.get(AggregateStatisticsRequest.Stats.MEAN),
		a1Resp.get(AggregateStatisticsRequest.Stats.MAX)
);

Retrieve Unique Values

// Find unique taxi vendor IDs
List<Record> a2Resp = kdb.aggregateUnique(TABLE_TAXI, "vendor_id", 0, GPUdb.END_OF_SET, null).getData();
System.out.println("Unique vendor IDs in the taxi trip table:");
for (Record vendor : a2Resp)
	System.out.println("\t* " + vendor.get("vendor_id"));

Report Number of Records per Group

// Find number of trips per vendor
List <String> colNames = Arrays.asList("vendor_id", "count(vendor_id)");
List<Record> a3Resp = kdb.aggregateGroupBy(
		TABLE_TAXI,
		colNames,
		0,
		GPUdb.END_OF_SET,
		GPUdb.options(
				AggregateGroupByRequest.Options.SORT_BY,
				AggregateGroupByRequest.Options.KEY
		)
).getData();
System.out.println("Trips per vendor:");
for (Record vendor : a3Resp)
	System.out.printf("\t%-6s %3d%n", vendor.get("vendor_id") + ":", vendor.get("count(vendor_id)"));

Generate Histogram

// Create a histogram for the different groups of passenger counts
float start = 1;
float end = 6;
float interval = 1;
List<Double> a4Resp = kdb.aggregateHistogram(
		TABLE_TAXI,
		"passenger_count",
		start,
		end,
		interval,
		null
).getCounts();

System.out.println("Passenger count groups by size:");
System.out.println("Passengers Total Trips");
System.out.println("========== ===========");
List<String> countGroups = Arrays.asList("1", "2", "3", "4", ">5");
for (int hgNum = 0; hgNum < a4Resp.size(); hgNum++)
	System.out.printf("%10s %11.0f%n", countGroups.get(hgNum), a4Resp.get(hgNum));

Joins

Joins allow you to link multiple tables together, along their relations, retrieving associated information from any or all of them. Tables can only be joined if they’re sharded similarly or replicated. All join types can be performed using the createJoinTable() method. An inner join returns only records that have matching values in both tables.

Inner Join

/* Retrieve cab ride transactions and the full name of the associated
 * vendor for rides having more than three passengers between April 1st
 * & 16th, 2015 */
kdb.createJoinTable(
		JOIN_TABLE_INNER,
		Arrays.asList(TABLE_TAXI + " as t", TABLE_PAYMENT + " as p"),
		Arrays.asList(
				"t.payment_id", "payment_type", "total_amount",
				"passenger_count", "vendor_id", "trip_distance"
		),
		Arrays.asList("t.payment_id = p.payment_id", "passenger_count > 3"),
		null
);

A left join returns all of the records an inner join does, but additionally, for each record in the table on the left side of the join that has no match along the relation to a record in the table on the right side of the join, a corresponding record will be returned with “left-side” columns populated with the “left-side” record data and the “right-side” columns populated with nulls. Note the usage of left join in the given expression.

Left Join

/* Retrieve cab ride transactions and the full name of the associated
 * vendor (if available--blank if vendor name is unknown) for
 * transactions with associated payment data, sorting by increasing
 * values of transaction ID. */
kdb.createJoinTable(
		JOIN_TABLE_LEFT,
		Arrays.asList(TABLE_TAXI + " as t", TABLE_VENDOR + " as v"),
		Arrays.asList("transaction_id", "pickup_datetime", "trip_distance", "t.vendor_id", "vendor_name"),
		Arrays.asList("left join t, v on (t.vendor_id = v.vendor_id)", "payment_id <> 0"),
		null
);

Full outer joins require both tables to be replicated or joined on their shard keys. Set merges that perform deduplication of records, like Union Distinct, Intersect, and Except also need to use replicated tables to ensure the correct results, so a replicated version of the taxi (taxi_trip_data_replicated) table is created at this point in the tutorial using createProjection().

Create Replicated Table for Full Outer Join

kdb.createProjection(
		TABLE_TAXI,
		TABLE_TAXI_REPLICATED,
		Arrays.asList(
				"transaction_id",
				"payment_id",
				"vendor_id",
				"pickup_datetime",
				"dropoff_datetime",
				"passenger_count",
				"trip_distance",
				"pickup_longitude",
				"pickup_latitude",
				"dropoff_longitude",
				"dropoff_latitude"
		),
		GPUdb.options(CreateProjectionRequest.Options.IS_REPLICATED, "true")
);

A full outer join returns all of the records a left join does, but additionally, for each record in the table on the right side of the join that has no match along the relation to a record in the table on the left side of the join, a corresponding record will be returned with “right-side” columns populated with the “right-side” record data and the “left-side” columns populated with nulls.

Full Outer Join

/* Retrieve the vendor IDs of known vendors with no recorded cab ride
 * transactions, as well as the vendor ID and number of transactions
 * for unknown vendors with recorded cab ride transactions */
kdb.createJoinTable(
		JOIN_TABLE_OUTER,
		Arrays.asList(TABLE_TAXI_REPLICATED + " as t", TABLE_VENDOR + " as v"),
		Arrays.asList("t.vendor_id as vendor_id", "v.vendor_id as vendor_id_1"),
		Arrays.asList("full_outer join t,v on ((v.vendor_id = t.vendor_id))"),
		null
);

Projections

You can create projections using the createProjection() method.

Create a Temporary Projection

// Create a projection containing all payments by credit card
kdb.createProjection(
		TABLE_PAYMENT,
		PROJECTION_EXAMPLE1,
		Arrays.asList(
				"payment_id", "payment_type", "credit_type",
				"payment_timestamp", "fare_amount", "surcharge",
				"mta_tax", "tip_amount", "tolls_amount", "total_amount"
		),
		GPUdb.options(CreateProjectionRequest.Options.EXPRESSION, "payment_type = 'Credit'")
);

To persist a projection:

Create a Permanent Projection

/* Create a persisted table with cab ride transactions greater than 5
 * miles whose trip started during lunch hours */
kdb.createProjection(
		TABLE_TAXI,
		PROJECTION_EXAMPLE2,
		Arrays.asList(
				"hour(pickup_datetime) as hour_of_day", "vendor_id",
				"passenger_count", "trip_distance"
		),
		GPUdb.options(
				CreateProjectionRequest.Options.EXPRESSION,
				"(hour(pickup_datetime) >= 11) AND " +
				"(hour(pickup_datetime) <= 14) AND " +
				"(trip_distance > 5)",
				CreateProjectionRequest.Options.PERSIST,
				CreateProjectionRequest.Options.TRUE
		)
);

Union, Intersect, & Except

Union can be used to combine homogeneous data sets into one larger data set. When calling the createUnion() method, a MODE of UNION or UNION_DISTINCT will both combine data sets, but only retain the records that are unique across the chosen columns, removing all duplicates. A MODE of UNION_ALL will combine data sets, retaining all records from the source data sets.

Set Union Retaining Duplicates

/* Calculate the average number of passengers, as well as the shortest,
 * average, and longest trips for all trips in each of the two time
 * periods--from April 1st through the 15th, 2015 and from April 16th
 * through the 23rd, 2015--and return those two sets of statistics in a
 * single result set. */
kdb.aggregateGroupBy(
		TABLE_TAXI,
		Arrays.asList(
				"avg(passenger_count) as avg_pass_count",
				"avg(trip_distance) as avg_trip_dist",
				"min(trip_distance) as min_trip_dist",
				"max(trip_distance) as max_trip_dist"
		),
		0,
		GPUdb.END_OF_SET,
		GPUdb.options(
				AggregateGroupByRequest.Options.EXPRESSION,
				"((pickup_datetime >= '2015-04-01') AND " +
				"(pickup_datetime <= '2015-04-15 23:59:59.999'))",
				AggregateGroupByRequest.Options.RESULT_TABLE,
				AGG_GRPBY_UNION_ALL_SRC1
		)
);
kdb.aggregateGroupBy(
		TABLE_TAXI,
		Arrays.asList(
				"avg(passenger_count) as avg_pass_count",
				"avg(trip_distance) as avg_trip_dist",
				"min(trip_distance) as min_trip_dist",
				"max(trip_distance) as max_trip_dist"
		),
		0,
		GPUdb.END_OF_SET,
		GPUdb.options(
				AggregateGroupByRequest.Options.EXPRESSION,
				"((pickup_datetime >= '2015-04-16') AND " +
				"(pickup_datetime  <= '2015-04-23 23:59:59.999'))",
				AggregateGroupByRequest.Options.RESULT_TABLE,
				AGG_GRPBY_UNION_ALL_SRC2
		)
);
kdb.createUnion(
		UNION_ALL_TABLE,
		Arrays.asList(AGG_GRPBY_UNION_ALL_SRC1, AGG_GRPBY_UNION_ALL_SRC2),
		Arrays.asList(
				Arrays.asList(
						"'2015-04-01 - 2015-04-15'",
						"avg_pass_count", "avg_trip_dist",
						"min_trip_dist", "max_trip_dist"
				),
				Arrays.asList(
						"'2015-04-16 - 2015-04-23'",
						"avg_pass_count", "avg_trip_dist",
						"min_trip_dist", "max_trip_dist"
				)
		),
		Arrays.asList(
				"pickup_window_range", "avg_pass_count",
				"avg_trip", "min_trip", "max_trip"
		),
		GPUdb.options(CreateUnionRequest.Options.MODE, CreateUnionRequest.Options.UNION_ALL)
);

Calling the createUnion() method with a MODE of INTERSECT will perform a set intersection, which will combine data sets but only include the records found in both data sets, removing duplicate result records. A MODE of INTERSECT_ALL will retain intersecting duplicates from both sets.

Set Intersection

/* Retrieve locations (as lat/lon pairs) that were both pick-up and
 * drop-off points */
kdb.createUnion(
		UNION_INTERSECT_TABLE,
		Arrays.asList(TABLE_TAXI_REPLICATED, TABLE_TAXI_REPLICATED),
		Arrays.asList(
				Arrays.asList("pickup_latitude", "pickup_longitude"),
				Arrays.asList("dropoff_latitude", "dropoff_longitude")
		),
		Arrays.asList("latitude", "longitude"),
		GPUdb.options(CreateUnionRequest.Options.MODE, CreateUnionRequest.Options.INTERSECT)
);

Calling the createUnion() method with a MODE of EXCEPT will perform a set except (subtraction), which will return records that appear in the first data set but not the second data set. Note that the data sets on each side of the except will have duplicates removed first, and then the set subtraction will be processed. A MODE of EXCEPT_ALL will retain duplicates from the first set.

Set Exception (Subtraction)

/* Show vendors that operate before noon, but not after noon: retrieve
 * the unique list of IDs of vendors who provided cab rides between
 * midnight and noon, and remove from that list the IDs of any vendors
 * who provided cab rides between noon and midnight */
kdb.createProjection(
		TABLE_TAXI_REPLICATED,
		PROJECTION_EXCEPT_SRC1,
		Arrays.asList("vendor_id"),
		GPUdb.options(
				CreateProjectionRequest.Options.EXPRESSION,
				"((HOUR(pickup_datetime) >= 0) AND (HOUR(pickup_datetime) <= 11))"
		)
);
kdb.createProjection(
		TABLE_TAXI_REPLICATED,
		PROJECTION_EXCEPT_SRC2,
		Arrays.asList("vendor_id"),
		GPUdb.options(
				CreateProjectionRequest.Options.EXPRESSION,
				"((HOUR(pickup_datetime) >= 12) AND (HOUR(pickup_datetime) <= 23))"
		)
);
kdb.createUnion(
		UNION_EXCEPT_TABLE,
		Arrays.asList(PROJECTION_EXCEPT_SRC1, PROJECTION_EXCEPT_SRC2),
		Arrays.asList(Arrays.asList("vendor_id"), Arrays.asList("vendor_id")),
		Arrays.asList("vendor_id"),
		GPUdb.options(CreateUnionRequest.Options.MODE, CreateUnionRequest.Options.EXCEPT)
);

Download & Run

Included below is a complete example containing all the above requests, the data file, output, compiled jar, and pom files.

To run the complete sample, ensure the taxi_trip_data.csv is in the correct location, given the direction here, and run the tutorial JAR as an executable jar. For instance, if running from the API project root:

Run Tutorial

java -jar target/docsite-tutorial-3.0-jar-with-dependencies.jar <url> <username> <password>

As this script creates a schema and several database objects within it, system admin permission is required to run it.

​Prerequisites

​Data File

​API Download

​Maven Download

​Manual Download

​File Hierarchy

​Connecting to the Database

​Creating a Schema

​Creating a Type

​Creating a Table

​Inserting Data

​Key/Value Record

​In-Line Record

​CSV

​Retrieving Data

​Updating Records

​Deleting Records

​Alter Table

​Indexes

​Dictionary Encoding

​Filters

​Aggregates

​Joins

​Projections

​Union, Intersect, & Except

​Download & Run

Prerequisites

Data File

API Download

Maven Download

Manual Download

File Hierarchy

Connecting to the Database

Creating a Schema

Creating a Type

Creating a Table

Inserting Data

Key/Value Record

In-Line Record

CSV

Retrieving Data

Updating Records

Deleting Records

Alter Table

Indexes

Dictionary Encoding

Filters

Aggregates

Joins

Projections

Union, Intersect, & Except

Download & Run