Inserting Data from Avro

The Inserting Data from Avro page describes inserting data from Avro into SQream and includes the following:

Overview
Making Avro Files Accessible to Workers
Preparing Your Table
Mapping Between SQream and Avro Data Types
Mapping Objects to Rows
Ingesting Data into SQream
Parameters
Best Practices
Additional Examples

Overview 

Avro is a well-known data serialization system that relies on schemas. Due to its flexibility as an efficient data storage method, SQream supports the Avro binary data format as an alternative to JSON. Avro files are represented using the Object Container File format, in which the Avro schema is encoded alongside binary data. Multiple files loaded in the same transaction are serialized using the same schema. If they are not serialized using the same schema, an error message is displayed. SQream uses the .avro extension for ingested Avro files.

Making Avro Files Accessible to Workers 

To give workers access to files every node must have the same view of the storage being used.

The following apply for Avro files to be accessible to workers:

For files hosted on NFS, ensure that the mount is accessible from all servers.
For HDFS, ensure that SQream servers have access to the HDFS name node with the correct user-id. For more information, see Using SQream in an HDFS Environment.
For S3, ensure network access to the S3 endpoint. For more information, see Inserting Data Using Amazon S3.

For more information about restricted worker access, see Workload Manager.

Preparing Your Table 

You can build your table structure on both local and foreign tables:

Creating a Table
Creating a Foreign Table

Creating a Table 

Before loading data, you must build the CREATE TABLE to correspond with the file structure of the inserted table.

The example in this section is based on the source nba.avro table shown below:

nba.avro
Name	Team	Number	Position	Age	Height	Weight	College	Salary
Avery Bradley	Boston Celtics	0.0	PG	25.0	6-2	180.0	Texas	7730337.0
Jae Crowder	Boston Celtics	99.0	SF	25.0	6-6	235.0	Marquette	6796117.0
John Holland	Boston Celtics	30.0	SG	27.0	6-5	205.0	Boston University
R.J. Hunter	Boston Celtics	28.0	SG	22.0	6-5	185.0	Georgia State	1148640.0
Jonas Jerebko	Boston Celtics	8.0	PF	29.0	6-10	231.0		5000000.0
Amir Johnson	Boston Celtics	90.0	PF	29.0	6-9	240.0		12000000.0
Jordan Mickey	Boston Celtics	55.0	PF	21.0	6-8	235.0	LSU	1170960.0
Kelly Olynyk	Boston Celtics	41.0	C	25.0	7-0	238.0	Gonzaga	2165160.0
Terry Rozier	Boston Celtics	12.0	PG	22.0	6-2	190.0	Louisville	1824360.0

The following example shows the correct file structure used to create the CREATE TABLE statement based on the nba.avro table:

CREATE TABLE ext_nba
(

     Name       TEXT(40),
     Team       TEXT(40),
     Number     BIGINT,
     Position   TEXT(2),
     Age        BIGINT,
     Height     TEXT(4),
     Weight     BIGINT,
     College    TEXT(40),
     Salary     FLOAT
 )
 WRAPPER avro_fdw
 OPTIONS
 (
   LOCATION =  's3://sqream-demo-data/nba.avro'
 );

Tip

An exact match must exist between the SQream and Avro types. For unsupported column types, you can set the type to any type and exclude it from subsequent queries.

Note

The nba.avro file is stored on S3 at s3://sqream-demo-data/nba.avro.

Creating a Foreign Table 

Before loading data, you must build the CREATE FOREIGN TABLE to correspond with the file structure of the inserted table.

The example in this section is based on the source nba.avro table shown below:

nba.avro
Name	Team	Number	Position	Age	Height	Weight	College	Salary
Avery Bradley	Boston Celtics	0.0	PG	25.0	6-2	180.0	Texas	7730337.0
Jae Crowder	Boston Celtics	99.0	SF	25.0	6-6	235.0	Marquette	6796117.0
John Holland	Boston Celtics	30.0	SG	27.0	6-5	205.0	Boston University
R.J. Hunter	Boston Celtics	28.0	SG	22.0	6-5	185.0	Georgia State	1148640.0
Jonas Jerebko	Boston Celtics	8.0	PF	29.0	6-10	231.0		5000000.0
Amir Johnson	Boston Celtics	90.0	PF	29.0	6-9	240.0		12000000.0
Jordan Mickey	Boston Celtics	55.0	PF	21.0	6-8	235.0	LSU	1170960.0
Kelly Olynyk	Boston Celtics	41.0	C	25.0	7-0	238.0	Gonzaga	2165160.0
Terry Rozier	Boston Celtics	12.0	PG	22.0	6-2	190.0	Louisville	1824360.0

The following example shows the correct file structure used to create the CREATE FOREIGN TABLE statement based on the nba.avro table:

CREATE FOREIGN TABLE ext_nba
(

     Name       TEXT(40),
     Team       TEXT(40),
     Number     BIGINT,
     Position   TEXT(2),
     Age        BIGINT,
     Height     TEXT(4),
     Weight     BIGINT,
     College    TEXT(40),
     Salary     FLOAT
 )
 WRAPPER avro_fdw
 OPTIONS
 (
   LOCATION =  's3://sqream-demo-data/nba.avro'
 );

Tip

An exact match must exist between the SQream and Avro types. For unsupported column types, you can set the type to any type and exclude it from subsequent queries.

Note

The nba.avro file is stored on S3 at s3://sqream-demo-data/nba.avro.

Note

The examples in the sections above are identical except for the syntax used to create the tables.

Mapping Between SQream and Avro Data Types 

Mapping between SQream and Avro data types depends on the Avro data type:

Primitive Data Types
Complex Data Types
Logical Data Types

Primitive Data Types 

The following table shows the supported Primitive data types:

Avro Type	SQream Type
Avro Type	Number	Date/Datetime	String	Boolean
`null`	Supported	Supported	Supported	Supported
`boolean`			Supported	Supported
`int`	Supported		Supported
`long`	Supported		Supported
`float`	Supported		Supported
`double`	Supported		Supported
`bytes`
`string`		Supported	Supported

Complex Data Types 

The following table shows the supported Complex data types:

Avro Type	SQream Type
Avro Type	Number	Date/Datetime	String	Boolean
`record`
`enum`			Supported
`array`
`map`
`union`	Supported	Supported	Supported	Supported
`fixed`

Logical Data Types 

The following table shows the supported Logical data types:

Avro Type	SQream Type
Avro Type	Number	Date/Datetime	String	Boolean
`decimal`	Supported		Supported
`uuid`			Supported
`date`		Supported	Supported
`time-millis`
`time-micros`
`timestamp-millis`		Supported	Supported
`timestamp-micros`		Supported	Supported
`local-timestamp-millis`
`local-timestamp-micros`
`duration`

Note

Number types include tinyint, smallint, int, bigint, real and float, and numeric. String types include text.

Mapping Objects to Rows 

When mapping objects to rows, each Avro object or message must contain one record type object corresponding to a single row in SQream. The record fields are associated by name to their target table columns. Additional unmapped fields will be ignored. Note that using the JSONPath option overrides this.

Ingesting Data into SQream 

This section includes the following:

Syntax
Example

Syntax 

Before ingesting data into SQream from an Avro file, you must create a table using the following syntax:

COPY [schema name.]table_name
  FROM WRAPPER fdw_name
;

After creating a table you can ingest data from an Avro file into SQream using the following syntax:

avro_fdw

Example 

The following is an example of creating a table:

COPY t
  FROM WRAPPER fdw_name
  OPTIONS
  (
    [ copy_from_option [, ...] ]
  )
;

The following is an example of loading data from an Avro file into SQream:

WRAPPER avro_fdw
OPTIONS
(
  LOCATION =  's3://sqream-demo-data/nba.avro'
);

For more examples, see Additional Examples.

Parameters 

The following table shows the Avro parameter:

Parameter	Description
`schema_name`	The schema name for the table. Defaults to `public` if not specified.

Best Practices 

Because external tables do not automatically verify the file integrity or structure, SQream recommends manually verifying your table output when ingesting Avro files into SQream. This lets you determine if your table output is identical to your originally inserted table.

The following is an example of the output based on the nba.avro table:

t=> SELECT * FROM ext_nba LIMIT 10;
Name          | Team           | Number | Position | Age | Height | Weight | College           | Salary
--------------+----------------+--------+----------+-----+--------+--------+-------------------+---------
Avery Bradley | Boston Celtics |      0 | PG       |  25 | 6-2    |    180 | Texas             |  7730337
Jae Crowder   | Boston Celtics |     99 | SF       |  25 | 6-6    |    235 | Marquette         |  6796117
John Holland  | Boston Celtics |     30 | SG       |  27 | 6-5    |    205 | Boston University |
R.J. Hunter   | Boston Celtics |     28 | SG       |  22 | 6-5    |    185 | Georgia State     |  1148640
Jonas Jerebko | Boston Celtics |      8 | PF       |  29 | 6-10   |    231 |                   |  5000000
Amir Johnson  | Boston Celtics |     90 | PF       |  29 | 6-9    |    240 |                   | 12000000
Jordan Mickey | Boston Celtics |     55 | PF       |  21 | 6-8    |    235 | LSU               |  1170960
Kelly Olynyk  | Boston Celtics |     41 | C        |  25 | 7-0    |    238 | Gonzaga           |  2165160
Terry Rozier  | Boston Celtics |     12 | PG       |  22 | 6-2    |    190 | Louisville        |  1824360
Marcus Smart  | Boston Celtics |     36 | PG       |  22 | 6-4    |    220 | Oklahoma State    |  3431040

Note

If your table output has errors, verify that the structure of the Avro files correctly corresponds to the external table structure that you created.

Additional Examples 

This section includes the following additional examples of loading data into SQream:

Omitting Unsupported Column Types
Modifying Data Before Loading
Loading a Table from a Directory of Avro Files on HDFS
Loading a Table from a Directory of Avro Files on S3

Omitting Unsupported Column Types 

When loading data, you can omit columns using the NULL as argument. You can use this argument to omit unsupported columns from queries that access external tables. By omitting them, these columns will not be called and will avoid generating a “type mismatch” error.

In the example below, the Position column is not supported due its type.

CREATE TABLE nba AS
   SELECT Name, Team, Number, NULL as Position, Age, Height, Weight, College, Salary FROM ext_nba;

Modifying Data Before Loading 

One of the main reasons for staging data using the EXTERNAL TABLE argument is to examine and modify table contents before loading it into SQream.

For example, we can replace pounds with kilograms using the CREATE TABLE AS statement

In the example below, the Position column is set to the default NULL.

CREATE TABLE nba AS
   SELECT name, team, number, NULL as Position, age, height, (weight / 2.205) as weight, college, salary
           FROM ext_nba
           ORDER BY weight;

Loading a Table from a Directory of Avro Files on HDFS 

The following is an example of loading a table from a directory of Avro files on HDFS:

CREATE FOREIGN TABLE ext_users
  (id INT NOT NULL, name TEXT(30) NOT NULL, email TEXT(50) NOT NULL)
WRAPPER avro_fdw
OPTIONS
  (
     LOCATION =  'hdfs://hadoop-nn.piedpiper.com/rhendricks/users/*.avro'
  );

CREATE TABLE users AS SELECT * FROM ext_users;

For more configuration option examples, navigate to the CREATE FOREIGN TABLE page and see the Parameters table.

Loading a Table from a Directory of Avro Files on S3 

The following is an example of loading a table from a directory of Avro files on S3:

CREATE FOREIGN TABLE ext_users
  (id INT NOT NULL, name TEXT(30) NOT NULL, email TEXT(50) NOT NULL)
WRAPPER avro_fdw
OPTIONS
  ( LOCATION = 's3://pp-secret-bucket/users/*.avro',
    AWS_ID = 'our_aws_id',
    AWS_SECRET = 'our_aws_secret'
   );

CREATE TABLE users AS SELECT * FROM ext_users;