# US 11,442,954 B2 · Techniques for accessing on-premise data sources from public cloud for designing data processing pipelines > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,442,954 B2 - Document ID: US11442954B2 - Status: Granted - Kind: B2 - Application number: 16/863,833 - Filed: 2020-04-30 - Published: 2021-11-04 - Granted: 2022-09-13 - Earliest claimed: 2020-04-30 - Assignees: Oracle International Corporation - Applicants: Oracle International Corporation - Inventors: Debajyoti Roy - Web page: https://patentgrep.com/patent/US11442954B2 ## CPC - G06F 16/254: {Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses} - G06F 7/582: {Pseudo-random number generators} - G06F 9/3867: {using instruction pipelines} - G06F 16/211: {Schema design and management} - G06F 16/2379: {Updates performed during online database operations; commit processing} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A system for simulating a dataset based on sample statistics, and generating pipeline instructions for a database using the simulated dataset, is disclosed. The system may be a cloud-based platform. The system can provide improved performance and security while designing and deploying Extract-Transform-Load (ETL) database pipelines to manage on-premises data. The system receives, from a remote client, sample statistics characterizing a distribution of data corresponding to a column of a database table. The system can generate, based on the received sample statistics, a simulated dataset representing the column of the database table. The simulated dataset may be generated using pseudo-random data values from a distribution with statistics matching the sample statistics. The system can build a simulated database relation based at least in part on the simulated dataset. The system can generate and deploy pipeline instructions using the simulated database relation. ## Claims ### Claim 1 A method, comprising: receiving, by a server and from a remote client, sample statistics describing data, the data corresponding to an attribute of a database relation; generating, on the server and based at least in part on the received sample statistics, a simulated dataset corresponding to the attribute of the database relation; building a simulated database relation based at least in part on the simulated dataset; generating, based at least in part on the simulated dataset, pipeline instructions associated with a database pipeline; and deploying the generated pipeline instructions to the remote client. ### Claim 2 (depends on 1) The method of claim 1, wherein the sample statistics characterize a distribution of the data corresponding to the attribute. ### Claim 3 (depends on 1) The method of claim 1, wherein the remote client is configured to: receive the pipeline instructions; and execute the pipeline instructions using the data corresponding to the attribute of the database relation. ### Claim 4 (depends on 1) The method of claim 1, wherein generating the simulated dataset further comprises generating pseudo-random data values according to a distribution, the distribution having population statistics matching the received sample statistics. ### Claim 5 (depends on 4) The method of claim 4, further comprising obtaining a seed value, and wherein generating the pseudo-random data values further comprises seeding a pseudo-random generator with at least the obtained seed value. ### Claim 6 (depends on 1) The method of claim 1, wherein the remote client is configured to determine the sample statistics describing the data. ### Claim 7 (depends on 1) The method of claim 1, further comprising: receiving, by the server and from the remote client, updated sample statistics describing updated data, the updated data corresponding to the attribute of the database relation; and updating, on the server and based at least in part on the updated sample statistics, the simulated dataset. ### Claim 8 (depends on 1) The method of claim 1, wherein the attribute comprises a column of an on-premises database table, and wherein the data corresponding to the attribute is stored within the column. ### Claim 9 (depends on 1) The method of claim 1, wherein the received sample statistics describing the data comprise information other than the data, and wherein a size of the received sample statistics does not depend on a size of the data. ### Claim 10 A system, comprising: one or more processors; and a memory configured to store computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to: receive, from a remote client, sample statistics describing data, the data corresponding to an attribute of a database relation; generate, based at least in part on the received sample statistics, a simulated dataset corresponding to the attribute of the database relation; build a simulated database relation based at least in part on the simulated dataset; generate, based at least in part on the simulated dataset, pipeline instructions associated with a database pipeline; and deploy the generated pipeline instructions to the remote client. ### Claim 11 (depends on 10) The system of claim 10, wherein the sample statistics characterize a distribution of the data corresponding to the attribute. ### Claim 12 (depends on 10) The system of claim 10, wherein generating the simulated dataset further comprises generating pseudo-random data values according to a distribution, the distribution having population statistics matching the received sample statistics, and wherein the processors are further caused to obtain a seed value, and wherein generating the pseudo-random data values further comprises seeding a pseudo-random generator with at least the obtained seed value. ### Claim 13 A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a processor, cause the processor to perform operations comprising: receiving, from a remote client, sample statistics describing data, the data corresponding to an attribute of a database relation; generating, based at least in part on the received sample statistics, a simulated dataset corresponding to the attribute of the database relation; building a simulated database relation based at least in part on the simulated dataset; generating, based at least in part on the simulated dataset, pipeline instructions associated with a database pipeline: and deploying the generated pipeline instructions to the remote client. ### Claim 14 (depends on 13) The non-transitory computer-readable medium of claim 13, wherein the operations further comprise: receiving, from the remote client, updated sample statistics describing updated data, the updated data corresponding to the attribute of the database relation; and updating, based at least in part on the updated sample statistics, the simulated dataset. ### Claim 15 (depends on 13) The non-transitory computer-readable medium of claim 13, wherein the attribute comprises a column of an on-premises database table, and wherein the data corresponding to the attribute is stored within the column. ### Claim 16 (depends on 13) The non-transitory computer-readable medium of claim 13, wherein the received sample statistics describing the data comprise information other than the data, and wherein a size of the received sample statistics does not depend on a size of the data.