6. A computer system for generating a cluster graph of a database, the database including a plurality of tables having a table join structure, wherein the table join structure is indicated by table join edges in a schema graph of the database, wherein each of the plurality of tables includes a corresponding set of records, the computer system comprising: a processor; and memory media, accessible to the processor, including processor executable program instructions, the program instructions including instructions to: determine, for each given table in the plurality of tables, nearest neighbor table join edges associated with each record in a sample of records from the given table; group the sample of records for each given table into clusters based on the nearest neighbor table join edges; identify cluster pairs, wherein a cluster pair corresponds to two clusters from different tables of the database, wherein the two clusters instantiate a common table join edge; weight the cluster pairs according to a number of records that instantiate the common table join edge; filter any cluster pairs weighted below a threshold weighting, wherein the filtering includes a process selected from excluding the cluster pairs weighted below the threshold and combining clusters in each cluster pair weighted below the threshold weighting with a different cluster; select a source cluster from a first table and a target cluster from a second table, wherein the first table and second tables are different tables; select a third table in the database, wherein the third table shares a table join edge with the first table; and determine a relative frequency, with respect to the first table, with which the second table is reached from the third table.
6. A computer system for generating a cluster graph of a database, the database including a plurality of tables having a table join structure, wherein the table join structure is indicated by table join edges in a schema graph of the database, wherein each of the plurality of tables includes a corresponding set of records, the computer system comprising: a processor; and memory media, accessible to the processor, including processor executable program instructions, the program instructions including instructions to: determine, for each given table in the plurality of tables, nearest neighbor table join edges associated with each record in a sample of records from the given table; group the sample of records for each given table into clusters based on the nearest neighbor table join edges; identify cluster pairs, wherein a cluster pair corresponds to two clusters from different tables of the database, wherein the two clusters instantiate a common table join edge; weight the cluster pairs according to a number of records that instantiate the common table join edge; filter any cluster pairs weighted below a threshold weighting, wherein the filtering includes a process selected from excluding the cluster pairs weighted below the threshold and combining clusters in each cluster pair weighted below the threshold weighting with a different cluster; select a source cluster from a first table and a target cluster from a second table, wherein the first table and second tables are different tables; select a third table in the database, wherein the third table shares a table join edge with the first table; and determine a relative frequency, with respect to the first table, with which the second table is reached from the third table. 7. The computer system of claim 6 , further comprising: a storage device; and a display device, wherein the program instructions include instructions to: limit a number of table join edges in the table join structure to a predetermined maximum; and display the cluster graph on the display device.