The following code examples both result in this run-time error:
Unable to create a constant value of type 'System.Object'. Only primitive types or enumeration types are supported in this context.
var venuename = (from v in db.Venues
where v.PropGroupID.Equals(propgroup)
select v.VenueName).SingleOrDefault();
var venuename = (from v in db.Venues
where v.PropGroupID.Equals(propgroup)
select v.VenueName).FirstOrDefault();
Removing "SingleOrDefault()" (or FirstOrDefault) results in this compile-time error:
Cannot implicitly convert type 'System.Linq.IQueryable' to 'string'
var venuename = (from v in db.Venues
where v.PropGroupID.Equals(propgroup)
select v.VenueName);
I want to return the text from the field VenueName (it is in SQL Server DB with data type = nvarchar(75)). PropGroupID is currently unique (but that is not enforced). Suggestions?
You can get the value from:
var venueName = db.Venues
.Where(x => x.PropGroupId.Equals(propgroup))
.FirstOrDefault(x => x.VenueName);
About removing the "FirstOrDefault", you can get more information about lazy loading:
Entity Framework Loading Related
Entities
LINQ To Entities and Lazy
Loading
Related
x = fopen('pm10_data.txt');
fseek(x, 8,0);
dat = fscanf (x,'%f',[2,1000]);
dat = transpose(dat);
a = dat(:,1);
b = dat(:,2);
[r,p] = cor_test (a,b)
fclose(x);
r
p
this is what i got,
r =
scalar structure containing the fields:
method = Pearson's product moment correlation
params = 76
stat = 6.2156
dist = t
pval = 2.5292e-08
alternative = !=
Run error
error: element number 2 undefined in return list
error: called from
tester.octave at line 7 column 6
Presumably you're referring to the cor_test function from the statistics package, even though you don't show loading this in your workspace.
According to the documentation of cor_test:
The output is a structure with the following elements:
PVAL The p-value of the test.
STAT The value of the test statistic.
DIST The distribution of the test statistic.
PARAMS The parameters of the null distribution of the test statistic.
ALTERNATIVE The alternative hypothesis.
METHOD The method used for testing.
If no output argument is given, the p-value is displayed.
This seems to be what you're getting too.
If you want the p value explicitly from that structure, you can access that as r.pval
The syntax [a, b, ...] = functionname( args, ... ) expects the function to return more than one argument, and capture all the returned arguments into the named variables (i.e. a, b, etc).
In this case, cor_test only returns a single argument, even though that argument is a struct (which means it has fields you can access).
The error you're getting effectively means you requested a second output argument p, but the function you're using does not return a second output argument. It only returns that struct you already captured in r.
I have a postgres database to which I read/write using JOOQ. One of my DB tables has a column of type JSON. When I try to insert data into this column using the query below, I get the error
Exception in thread "main" org.jooq.exception.DataAccessException: SQL [update "public"."asset_state" set "sites_as_json" = ?]; ERROR: column "sites_as_json" is of type json but expression is of type character varying
Hint: You will need to rewrite or cast the expression.
Below is the code for inserting data into the column
SiteObj s1 = new SiteObj();
s1.setId("1");
s1.setName("Site1");
s1.setGeofenceType("Customer Site");
SiteObj s2 = new SiteObj();
s2.setId("2");
s2.setName("Site2");
s2.setGeofenceType("Customer Site");
List<SiteObj> sitesList = Arrays.asList(s1, s2);
int result = this.dsl.update(as).set(as.SITES_AS_JSON, LambdaUtil.convertJsonToStr(sitesList)).execute();
The call LambdaUtil.convertJsonToStr(sitesList) outputs a string that looks like this...
[{"id":"1","name":"Site1","geofenceType":"Customer Site"},{"id":"2","name":"Site2","geofenceType":"Customer Site"}]
What do I need to do to be able to insert into the JSON column?
Current jOOQ versions
jOOQ natively supports JSON and JSONB data types. You shouldn't need to have to do anything custom.
Historic answer
For jOOQ to correctly bind your JSON string to the JDBC driver, you will need to implement a data type binding as documented here:
https://www.jooq.org/doc/latest/manual/code-generation/custom-data-type-bindings
The important bit is the fact that your generated SQL needs to produce an explicit type cast, for example:
#Override
public void sql(BindingSQLContext<JsonElement> ctx) throws SQLException {
// Depending on how you generate your SQL, you may need to explicitly distinguish
// between jOOQ generating bind variables or inlined literals.
if (ctx.render().paramType() == ParamType.INLINED)
ctx.render().visit(DSL.inline(ctx.convert(converter()).value())).sql("::json");
else
ctx.render().sql("?::json");
}
I want to catch and handle SAPSQL_DATA_LOSS in my ABAP code.
I tried this:
try.
SELECT *
FROM (rtab_name) AS rtab
WHERE (sub_condition)
into table #<sub_result>
.
catch SAPSQL_DATA_LOSS into error.
...
endtry.
But above code is not valid. I get this message:
Type "SAPSQL_DATA_LOSS" is not valid
And I tried this:
catch SYSTEM-EXCEPTIONS SAPSQL_DATA_LOSS = 123.
SELECT *
...
.
endcatch.
if sy-subrc = 123.
...
endif.
But above code gives me:
Instead of "SAPSQL_DATA_LOSS" expected "system-exception" (translated from german to english by me)
How to catch SAPSQL_DATA_LOSS?
This question is not about "why does this exception happen?". This is already solved. My code should handle the exception.
SAPSQL_DATA_LOSS is a runtime error.
As SAPSQL_DATA_LOSS is not a class-based exception, it is not possible to catch it using try catch.
As SAPSQL_DATA_LOSS is not a catchable runtime error, it is not possible to catch it using try catch SYSTEM-EXCEPTIONS.
see the below catchable runtime errors.
https://help.sap.com/doc/abapdocu_751_index_htm/7.51/en-US/abenueb-abfb-sysexc.htm
After some tries I can propose you a possible solution.
This is a workaround:
I don't know if it can be applied to your case, since it needs the select statement to be wrapped into an RFC function module !
The main point is that a short dump (message type X) CAN be handled in RFC calls.
So using an RFC (CALL FUNCTION 'xxxxx' destination 'NONE' for example) and using special exception SYSTEM_FAILURE, the system does not terminate the caller program, but instead it returns a SY-SUBRC > 0 with the Short dump informations in system message fields (SY-MSGxx).
STEPS
Create a Function module (RFC enabled) with your select statement input + the row type of the result table. (All parameters passed by value)
You need this last parameter since generic tables can't be passed in RFC (no "TYPE ANY TABLE" allowed)
FUNCTION Z_DYN_SEL .
*"----------------------------------------------------------------------
*"*"Local interface:
*" IMPORTING
*" VALUE(RTAB_NAME) TYPE TABNAME16
*" VALUE(SUB_CONDITION) TYPE STRING
*" VALUE(RESULT_TYPE) TYPE STRING
*"----------------------------------------------------------------------
* RTAB_NAME: DB Table
* SUB_CONDITION: WHERE Condition
* RESULT_TYPE: The ROW type of the internal table
field-symbols <sub_result> type any table.
* DEFINE LOCAL DYNAMIC TABLE TO STORE THE RESULT
data: lr_res type ref to data.
create data lr_res type standard table of (result_type).
assign lr_res->* to <sub_result>.
* DYNAMIC SELECT
select *
from (rtab_name) as rtab
where (sub_condition)
into table #<sub_result>.
* EXPORT RESULT TO A MEMORY ID, SO IT CAN BE RETRIEVED BY CALLER
export res = <sub_result> to memory id 'RES'.
Main program:
In this caller example some parameters are passed to the RFC.
KTOKD field (should be 4 chars long) is passed with a char10 value (producing your short dump).
If ANY Dump is triggered inside the function, we can now handle it.
If everything went fine, IMPORT result from the EXPORT statement inside the RFC
field-symbols <sub_result> type any table.
data: lr_res type ref to data.
create data lr_res type standard table of KNA1.
assign lr_res->* to <sub_result>.
data lv_msg type char255.
call function 'Z_DYN_SEL' destination 'NONE'
exporting
rtab_name = 'KNA1'
sub_condition = `KTOKD = 'D001xxxxxx'`
result_type = 'KNA1'
exceptions
system_failure = 1 message lv_msg.
if sy-subrc = 0.
import res = <sub_result> from memory id 'RES'.
else.
write: / lv_msg.
write : / sy-msgid, sy-msgno, sy-msgty, sy-msgv1, sy-msgv2, sy-msgv3, sy-msgv4.
endif.
RESULTS
After the RFC call in case of a short dump in the select statement, the program is not terminated and the following pieces of information are available
SY-SUBRC = 1
lv_msg is the error text (Data was lost while copying a value.)
Sy-msgid = 00
Sy-msgno = '341'
Sy-msgty = 'X'
Sy-msgv1 = 'SAPSQL_DATA_LOSS'
Given there is a dataset of messages, defined by following code:
case class Message(id: Int, value: String)
var messages = Seq(
(0, """{"action":"update","timestamp":"2017-10-05T23:01:19Z"}"""),
(1, """{"action":"update","timestamp":"2017-10-05T23:01:19Z"}""")
).toDF("id", "value").as[Message]
var schema = new StructType().add("action", StringType).add("timestamp", TimestampType)
var res = messages.select(
from_json(col("value").cast("string"), schema)
)
+------------------------------------+
|jsontostructs(CAST(value AS STRING))|
+------------------------------------+
| [update,2017-10-0...|
| [update,2017-10-0...|
What is the best way to access the schema information in a plain map function. The function itself returns a row which has lost all the Type infos. In order to reach to the values one has to specify the type again e.g
res.head().getStruct(0).getValuesMap[TimestampType](Seq("timestamp"))
=> Map[String,org.apache.spark.sql.types.TimestampType] = Map(timestamp -> 2017-10-06 01:01:19.0)
or
res.head().getStruct(0).getString(0)
=> res20: String = update
Is there some better way to access the raw json data without spark sql aggregation functions?
As a rule of thumb:
To use collection API (map, flatMap, mapPartitions, groupByKey, etc.) use strongly typed API - define record type (case class works the best) which reflects the schema and use Encoders to convert things back and forth:
case class Value(action: String, timestamp: java.sql.Timestamp)
case class ParsedMessage(id: Int, value: Option[Value])
messages.select(
$"id", from_json(col("value").cast("string"), schema).alias("value")
).as[ParsedMessage].map(???)
With Dataset[Row] stay with high level SQL / DataFrame API (select, where, agg, groupBy)
I'm reading a simple CSV file with Filehelpers - the file is just a key, value pair. (string, int64)
The f# type I've written for this is:
type MapVal (key:string, value:int64) =
new()= MapVal("",0L)
member x.Key = key
member x.Value = value
I'm missing something elementary here, but FileHelpers always assumes the order of fields to be the reverse of what I've specified - as in Value, Key.
let dfe = new DelimitedFileEngine(typeof<MapVal>)
let recs = dfe.ReadFile(#"D:\e.dat")
recs |> Seq.length
What am I missing here?
The order of primary constructor parameters doesn't necessarily determine the order that fields occur within a type (in fact, depending on how the parameters are used, they may not even result in a field being generated). The fact that FileHelpers doesn't provide a way to use properties instead of fields is unforunate, in my opinion. If you want better control over the physical layout of the class, you'll need to declare the fields explicitly:
type MapVal =
val mutable key : string
val mutable value : int64
new() = { key = ""; value = 0L }
new(k, v) = { key = k; value = v }
member x.Key = x.key
member x.Value = x.value
The library uses the order of the field in the declaration, but looks like that F# words different, in the last the last stable version of the library you can use the [FieldOrder(1)] attribute to provide the order of the fields.
http://teamcity.codebetter.com/viewLog.html?buildId=lastSuccessful&buildTypeId=bt66&tab=artifacts&guest=1
Cheers