将数据从 Siebel 数据库提取到 Dat 文件和临时表
我正在研究一项新要求，而且我对此还很陌生。所以寻求你的帮助。 要求 - 从 Siebel 基表（S_ORG_EXT、S_CONTACT、S_PROD_INT）中，我必须导出数据并需要放入两个临时表（S1 和 S2）中，并且从这些临时表中，我需要创建以管道分隔的 dat 文件，其中还包括行计数。对于暂存表 S1，我们应该有帐户及其关联的联系人；对于 S2，我们应该有帐户及其关联的联系人和产品。
我应该如何处理这个问题。我是否需要直接使用 Informatica 作业从 Siebel 基表中提取数据，或者需要运行 EIM 导出作业以获取 EIM 表中的数据并从那里到临时表。
请帮助我知道我应该走哪条路。
I am working on a new requirment and I am new into this. So seeking your help.
Requriment - From Siebel base tables (S_ORG_EXT,S_CONTACT,S_PROD_INT) I have to export data and need to put into two staging tables (S1 and S2) and from these staging tables I need to create dat files pipe delimited that include row count also. For staging table S1, we should have Accounts with their associated contacts and for S2, we should have account with its associated contact and Product.
How should I need to go about this. Should I need to use Informatica job directly to pull data from Siebel base tables or need to run EIM export job to get data in EIM table and from there to staging table.
Kindly help me know which way I should go.
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使用 Informatica 直接访问基表，将提取限制为仅您需要的行和列。
我建议在将它们加载到暂存表之前将它们卸载到平面文件（如果暂存表加载中出现问题，它可以为您提供恢复点，并且意味着您不必再次访问 Siebel DB）。
然后，您可以从那里卸载临时表，或者仅使用平面文件提取来生成带行数的分隔文件。
我倾向于支持具有合理恢复点的模块化进程，而不是通过“流式传输”数据来获得（可以说）更快的执行时间，所以这就是我要做的（每个映射一个）：
如果临时表的加载只是出于审计目的等，您可以将步骤 5 基于步骤 2 中创建的文件，然后您可以同时执行阶段 (3) 和阶段 (5)，这可能会减少总体运行时间。
如果这是一次性过程，或者您只是想快速编写它，则可以跳过编写平面文件，而只需在一两个映射中完成所有操作。但我不会这样做，因为
a) 测试更困难，
b) 恢复点更少。
干杯!
Access the base tables directly using Informatica, limiting the extract to only the rows and columns you need.
I'd recommend unloading these to flat files before loading them into the Staging Tables (it gives you a point of recovery if something goes wrong in your Staging Table load, and means you don't have to hit the Siebel DB again).
Then from there you can either unload the staging tables, or just use your flat file extract, to generate your delimited files with row counts.
I tend to favour modular processes, with sensible recovery points, over 'streaming' the data through for (arguably) faster execution time, so here's what I'd do (one mapping for each):
If the loading of a staging table is only for audit purposes etc, and you can base Step 5 on the files you created in Step 2, then you could perform stage (3) concurrently with stage (5), which may reduce overall runtime.
If this is a one-off process, or you just want to write it in a hurry, you could skip writing out the flat files and just do it all in one or two mappings. I wouldn't do this though, because
a) it's harder to test and
b) there are fewer recovery points.
Cheers!