Avro

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.

Foreign Data Wrapper Prerequisites

Before proceeding, ensure the following Foreign Data Wrapper (FDW) prerequisites:

  • File Existence: Verify that the file you are ingesting data from exists at the specified path.

  • Path Accuracy: Confirm that all path elements are present and correctly spelled. Any inaccuracies may lead to data retrieval issues.

  • Bucket Access Permissions: Ensure that you have the necessary access permissions to the bucket from which you are ingesting data. Lack of permissions can hinder the data retrieval process.

  • Wildcard Accuracy: If using wildcards, double-check their spelling and configuration. Misconfigured wildcards may result in unintended data ingestion.

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

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

PG

25

44714

180

Texas

7730337

Jae Crowder

Boston Celtics

99

SF

25

44718

235

Marquette

6796117

John Holland

Boston Celtics

30

SG

27

44717

205

Boston University

R.J. Hunter

Boston Celtics

28

SG

22

44717

185

Georgia State

1148640

Jonas Jerebko

Boston Celtics

8

PF

29

44722

231

5000000

Amir Johnson

Boston Celtics

90

PF

29

44721

240

12000000

Jordan Mickey

Boston Celtics

55

PF

21

44720

235

LSU

1170960

Kelly Olynyk

Boston Celtics

41

C

25

36708

238

Gonzaga

2165160

Terry Rozier

Boston Celtics

12

PG

22

44714

190

Louisville

1824360

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

PG

25

44714

180

Texas

7730337

Jae Crowder

Boston Celtics

99

SF

25

44718

235

Marquette

6796117

John Holland

Boston Celtics

30

SG

27

44717

205

Boston University

R.J. Hunter

Boston Celtics

28

SG

22

44717

185

Georgia State

1148640

Jonas Jerebko

Boston Celtics

8

PF

29

44722

231

5000000

Amir Johnson

Boston Celtics

90

PF

29

44721

240

12000000

Jordan Mickey

Boston Celtics

55

PF

21

44720

235

LSU

1170960

Kelly Olynyk

Boston Celtics

41

C

25

36708

238

Gonzaga

2165160

Terry Rozier

Boston Celtics

12

PG

22

44714

190

Louisville

1824360

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

The following table shows the supported Primitive data types:

Avro Type

SQream 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

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

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

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 foreign 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 foreign table structure that you created.

Additional Examples

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

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 foreign 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 FOREIGN 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 FOREIGN 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;