teradata

How can i search for a particular date for eg: '2013-10-22' from teradata timestamp(6) field? sel * from table A where date = '2013-10-22'; I tried the above query which is throwing error. Please help! You may try like this:- sel * from table A where date = date '2013-10-22'; Since in ANSI standard form (must be preceded by the keyword DATE) Check out this Something like this: where YourTimestampField >= {d '2013-10-22'} and YourTimestampField < {d '2013-10-23'} And more formally: select * from table A where cast(timestamp_column as date) = date '2013-10-22'; I'm guessing that you were just

I'm using Teradata, I have a table like this ID String 123 Jim 123 John 123 Jane 321 Jill 321 Janine 321 Johan I want to query the table so I get ID String 123 Jim, John, Jane 321 Jill, Janine, Johan I tried partition but there can be many names. How do I get this result. Even, to point me in the right direction would be great. Unfortunately there's no PIVOT in Teradata (only a TD_UNPIVOT in 14.10). If you got luck there's an aggregate UDF at your site to do a group concat (probably low possibility). Otherwise there are two options: recursion or aggregation. If the maximum number of rows per

I need to extract a table from Teradata (read-only access) to parquet with Scala (2.11) / Spark (2.1.0). I'm building a dataframe that I can load successfully val df = spark.read.format("jdbc").options(options).load() But df.show gives me a NullPointerException: java.lang.NullPointerException at org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter.write(UnsafeRowWriter.java:210) I did a df.printSchema and I found out that the reason for this NPE is that the dataset contains null values for (nullable = false) columns (it looks like Teradata is giving me wrong information). Indeed,

I'm using the PyTd teradata module to query data from Teradata and want to read it into a Pandas DataFrame import teradata import pandas as pd # teradata connection udaExec = teradata.UdaExec(appName="Example", version="1.0", logConsole=False) session = udaExec.connect(method="odbc", system="", username="", password="") # Create empty dataframe with column names query = session.execute("SELECT TOP 1 * FROM table") cols = [str(d[0]) for d in query.description] df = pd.DataFrame(columns=cols) # Read data into dataframe for row in session.execute("SELECT * FROM table"): print type(row) df.append

Has anyone found a way to read a Teradata query into a Pandas dataframe? It looks like SQLAlchemy does not have a Teradata dialect. http://docs.sqlalchemy.org/en/latest/dialects/ http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_sql.html I did it using read_sql . Below id the code snip : def dqm() : conn_rw = create_connection() dataframes = [] srcfile = open('srcqueries.sql', 'rU').read() querylist = srcfile.split(';') querylist.pop() for query in querylist : dataframes.append(pd.read_sql(query, conn_rw)) close_connection(conn_rw) return dataframes,querylist You can create