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https://issues.apache.org/jira/browse/DRILL-5152?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15806752#comment-15806752
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ASF GitHub Bot commented on DRILL-5152:
---------------------------------------
Github user sohami commented on a diff in the pull request:
https://github.com/apache/drill/pull/708#discussion_r95047914
--- Diff:
exec/java-exec/src/main/java/org/apache/drill/exec/store/mock/MockGroupScanPOP.java
---
@@ -104,44 +102,46 @@ public String toString() {
}
@JsonInclude(Include.NON_NULL)
- public static class MockColumn{
+ public static class MockColumn {
@JsonProperty("type") public MinorType minorType;
public String name;
public DataMode mode;
public Integer width;
public Integer precision;
public Integer scale;
-
+ public String generator;
+ public Integer repeat;
@JsonCreator
- public MockColumn(@JsonProperty("name") String name,
@JsonProperty("type") MinorType minorType, @JsonProperty("mode") DataMode mode,
@JsonProperty("width") Integer width, @JsonProperty("precision") Integer
precision, @JsonProperty("scale") Integer scale) {
--- End diff --
Same here - for overloading constructor.
> Enhance the mock data source: better data, SQL access
> -----------------------------------------------------
>
> Key: DRILL-5152
> URL: https://issues.apache.org/jira/browse/DRILL-5152
> Project: Apache Drill
> Issue Type: Improvement
> Components: Tools, Build & Test
> Affects Versions: 1.9.0
> Reporter: Paul Rogers
> Assignee: Paul Rogers
> Priority: Minor
>
> Drill provides a mock data storage engine that generates random data. The
> mock engine is used in some older unit tests that need a volume of data, but
> that are not too particular about the details of the data.
> The mock data source continues to have use even for modern tests. For
> example, the work in the external storage batch requires tests with varying
> amounts of data, but the exact form of the data is not important, just the
> quantity. For example, if we want to ensure that spilling happens at various
> trigger points, we need to read the right amount of data for that trigger.
> The existing mock data source has two limitations:
> 1. It generates only "black/white" (alternating) values, which is awkward for
> use in sorting.
> 2. The mock generator is accessible only from a physical plan, but not from
> SQL queries.
> This enhancement proposes to fix both limitations:
> 1. Generate a uniform, randomly distributed set of values.
> 2. Provide an encoding that lets a SQL query specify the data to be generated.
> Example SQL query:
> {code}
> SELECT id_i, name_s50 FROM `mock`.employee_10K;
> {code}
> The above says to generate two fields: INTEGER (the "_i" suffix) and
> VARCHAR(50) (the "_s50") suffix; and to generate 10,000 rows (the "_10K"
> suffix on the table.)
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