Data dictionary in sql server

ProblemThis tutorial will demonstrate how to migrate via JSON key-value pairs from a Python dictionary object to a SQL Server table. It will provide an in-depth review of how the key-value pairs are originally stored in Python, transformed to JSON, and exported to a file along with a use case example that reinforces how to import JSON data from a file and display the data within SQL Server.SolutionJSON (JavaScript Object Notation) is a popular open file format for exchanging data between applications as well as receiving data from a server. Because of the widespread adoption of JSON for exchanging data, it is increasingly important for SQL Server administrators to become familiar with how to retrieve and save JSON data for input to SQL Server tables. Also, SQL Server administrators may participate in projects for receiving content in JSON data files originating from other applications, such as Yahoo Finance. This tip presents a use case example for retrieving key-value paired data from Yahoo Finance with Python in order to export the key-value pairs to a file with a JSON data format for retrieval and saving in a SQL Server table.Summary of the use casePython is especially prized for its ability to interface with various application programming interfaces, such as those from Yahoo Finance for financial data and the National Oceanic and Atmospheric Administration for historical weather data. A recent MSSQLTips.com tip includes coverage of the yfinance library for use with Python. The yfinance library for Python can facilitate downloading historical price and volume data as well as fundamental data, such as number of employees, total public shares available for trading (float), and the number of shares shorted in a security. The fundamental data is available for each security via a Python dictionary object.The dictionary object is for storing ordered key-value pairs

The Report Writer module enables you to produce ad hoc reports in the format you require. The menu driven design provides access to all system data with no programming skills required. Reports can be sent to the printer, screen preview or an ASCII file. Data can be read and written back to the database facilitating mass updates. Data from 3rd party sources can be used in reports. Data can also be exported to third party software such as spreadsheets, word processors, databases, etc. The Report Writer does not have any logic to physically create SQL tables (i.e. the table definition or the columns and their data types). The Report Writer cannot write any new rows to an existing SQL server table. It can only be used to update existing rows in a SQL table. Implementation The Report Writer module uses its own data dictionary and not the standard data dictionary. For this reason, before you can use the SYSPRO Report Writer, you must use the Data Dictionary Import Wizard program to create the Report Writer Data Dictionary from the standard dictionary supplied with SYSPRO. This applies irrespective of whether you are using a C-ISAM or a SQL Server-based system. The standard data dictionary contains all the table names, columns and table linkages required for your reports. The import program uses files in the Base/dd directory to create the data dictionary. Importing the Standard Data Dictionary does not have any effect on your data files. Even if you have a previous version of the Report Writer installed, we recommend that you re-import the standard data dictionary to ensure that you have the most up-to-date definition of tables and columns. It is advisable to re-import the data dictionary every time a new version of the software is installed. Once you have created the Report Writer data dictionary, you can optionally use: the Browse on Data Dictionary Tables program to amend the Report Writer data dictionary tables. You should never amend the standard data dictionary. the Data Dictionary Table Listing program to print the details of data dictionary tables. the Browse on Data Dictionary Columns program to create and maintain the Report Writer data dictionary column definitions. the Browse on Data Dictionary Linkages program to define how tables are logically linked. By linking a table, the columns available in the linked table can be used when creating a report. SQL vs C-ISAM The

Skip to main content This browser is no longer supported. Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support. sys.pdw_nodes_column_store_dictionaries (Transact-SQL) Article03/03/2023 In this article -->Applies to: Azure Synapse Analytics Analytics Platform System (PDW)Contains a row for each dictionary used in columnstore indexes. Dictionaries are used to encode some, but not all data types, therefore not all columns in a columnstore index have dictionaries. A dictionary can exist as a primary dictionary (for all segments) and possibly for other secondary dictionaries used for a subset of the column's segments.Column nameData typeDescriptionpartition_idbigintIndicates the partition ID. Is unique within a database.hobt_idbigintID of the heap or B-tree index (HoBT) for the table that has this columnstore index.column_idintID of the columnstore column.dictionary_idintId of the dictionary.versionintVersion of the dictionary format.typeintDictionary type: 1 - Hash dictionary containing int values 2 - Not used 3 - Hash dictionary containing string values 4 - Hash dictionary containing float valueslast_idintThe last data id in the dictionary.entry_countbigintNumber of entries in the dictionary.on_disk_sizebigintSize of dictionary in bytes.pdw_node_idintUnique identifier of a Azure Synapse Analytics node.PermissionsRequires VIEW SERVER STATE permission.See AlsoAzure Synapse Analytics and Parallel Data Warehouse Catalog ViewsCREATE COLUMNSTORE INDEX (Transact-SQL)sys.pdw_nodes_column_store_segments (Transact-SQL)sys.pdw_nodes_column_store_row_groups (Transact-SQL) --> Feedback Additional resources In this article

Try: sql = "drop table t1;" print ( sql ) stmt = IfxPy.exec_immediate(conn, sql) except: print ('FYI: drop table failed') i = 0 for sql in SetupSqlSet: i += 1 print (sql) stmt = IfxPy.exec_immediate(conn, sql) # The first record executed is for create table i -= 1 # Select records sql = "SELECT * FROM t1" stmt = IfxPy.exec_immediate(conn, sql) dictionary = IfxPy.fetch_both(stmt) rc = 0 while dictionary != False: rc += 1 print ("-- Record {0} --".format(rc)) print ("c1 is : ", dictionary[0]) print ("c2 is : ", dictionary[1]) print ("c3 is : ", dictionary["c3"]) print ("c4 is : ", dictionary[3]) print (" ") dictionary = IfxPy.fetch_both(stmt) print() print( "Total Record Inserted {}".format(i) ) print( "Total Record Selected {}".format(rc) ) # Free up memory used by result and then stmt too IfxPy.free_result(stmt) IfxPy.free_stmt (stmt) IfxPy.close(conn) print ("Done")####### Run the sample function ######my_Sample()Param Binding of Basic Data Types# Sample2.pyimport IfxPydef my_Sample(): ConStr = "SERVER=ids0;DATABASE=db1;HOST=127.0.0.1;SERVICE=9088;UID=informix;PWD=xxxxx;" try: # netstat -a | findstr 9088 conn = IfxPy.connect( ConStr, "", "") except Exception as e: print ('ERROR: Connect failed') print ( e ) quit() try: sql = "drop table t1;" print ( sql ) stmt = IfxPy.exec_immediate(conn, sql) except: print ('FYI: drop table failed') sql = "create table t1 ( c1 int, c2 char(20), c3 int, c4 int ) ;" stmt = IfxPy.exec_immediate(conn, sql) sql = "INSERT INTO t1 (c1, c2, c3, c4) VALUES ( ?, ?, ?, ? )" stmt = IfxPy.prepare(conn, sql) c1 = None c2 = None c3 = None