kdb

问题 Consider the following table: `Keys `Values `A`B `V1`V2 `C`D`E `V1`V2`V3`V4 I want to flatten the Keys column only such that each key is mapped to the corresponding Values. The result should be: `Keys `Values `A `V1`V2 `B `V1`V2 `C `V1`V2`V3`V4 `D `V1`V2`V3`V4 `E `V1`V2`V3`V4 ungroup function applies ungroup to all columns, in this case I want to apply to Keys column alone. 回答1: Few different ways you can go about this, below is one way - ungroupCol:{[tbl;col] @[tbl where count each tbl col

问题 Thanks in advance for the help. I am new to kdb/q, coming from a Python and C++ background. Just a simple syntax question: I have a string with fields and their corresponding values pp_str: "field_1:abc field_2:xyz field_3:kdb" I wrote an atomic (scalar) function to extract the value of a given field. get_field_value: {[field; pp_str] pp_fields: " " vs pp_str; pid_field: pp_fields[where like[pp_fields; field,":*"]]; start_i: (pid_field[0] ss ":")[0] + 1; end_i: count pid_field[0]; indices:

问题 Thanks in advance for the help. I am new to kdb/q, coming from a Python and C++ background. Just a simple syntax question: I have a string with fields and their corresponding values pp_str: "field_1:abc field_2:xyz field_3:kdb" I wrote an atomic (scalar) function to extract the value of a given field. get_field_value: {[field; pp_str] pp_fields: " " vs pp_str; pid_field: pp_fields[where like[pp_fields; field,":*"]]; start_i: (pid_field[0] ss ":")[0] + 1; end_i: count pid_field[0]; indices:

问题 I am new to kdb and researching it for a use case to generate time series data using a table of various function inputs. Each row of the table consists of function inputs keyed by an id and segment and will call one function per row. I have figured out how to identify which function albeit using brute force nested conditions. My question is 2 part How does one employ kicking off the execution of these functions? Once the time series data is generated for each id and segment, how best can the

问题 I am new to kdb and researching it for a use case to generate time series data using a table of various function inputs. Each row of the table consists of function inputs keyed by an id and segment and will call one function per row. I have figured out how to identify which function albeit using brute force nested conditions. My question is 2 part How does one employ kicking off the execution of these functions? Once the time series data is generated for each id and segment, how best can the

问题 I am new to kdb and researching it for a use case to generate time series data using a table of various function inputs. Each row of the table consists of function inputs keyed by an id and segment and will call one function per row. I have figured out how to identify which function albeit using brute force nested conditions. My question is 2 part How does one employ kicking off the execution of these functions? Once the time series data is generated for each id and segment, how best can the

问题 I am trying to load the data for each date and then sort the sym column and apply the parted attribute. But I don’t know how to use the .Q.dpft function to save to the same table? There is a trade table in hdb. Here is my function: \l dbdir; test:{ trade:select from trade where date = x; trade:`sym xasc trade; .Q.dpft[dbdir;x;`sym;`trade]}each date; Doesn’t seem to be working though. The error is ``trade` 回答1: I think you need to pass the table trade & dbdir as arguments to your function

来源： https://stackoverflow.com/questions/64115623/parallel-execution-blocking-receive-deferred-synchronous

来源： https://stackoverflow.com/questions/64109959/on-parallel-execution-which-side-reports-about-an-error

来源： https://stackoverflow.com/questions/64109959/on-parallel-execution-which-side-reports-about-an-error