# Namespace Summary:
# =================
#
# sldg.source.jdbc.url:
#  Connection URL (jdbc:) to source table (required; read-only OK)
#
# sldg.source.info.xyz:
#  Connection property xyz is prefixed with sldg.source.info.
#
# sldg.source.jdbc.driver:
#  JDBC driver class name needed to load above jdbc URL (optional)
#
# sldg.source.jdbc.driver.classpath:
#  Path to .jar bundle containing the named driver class (optional)
#
# sldg.source.query.size:
#  "SELECT COUNT(*)" from source table query (required)
#
# sldg.source.query.row:
#  "SELECT" by row-number prepared-statement query (required)
#  Note however you design this, your row-nums must range [1, size] (no gaps)
#
# sldg.source.salt.seed:
#  Secret 64-char hex value seed for generating table-cell salts by row/col coordinates
#  Note this value should not be changed or lost. It protects individual table-cell
#  values from rainbow attacks (reverse-engineering a value from its hash).
#
# sldg.hash.jdbc.url:
#  Connection URL to DB the tracking hash-ledger lives in (optional)
#  If not set, then the hash-ledger lives in the same DB as the source-table
#
# sldg.hash.info.xyz:
#  Connection property xyz is prefixed with sldg.hash.info.
#
# sldg.hash.jdbc.driver:
#  JDBC driver class name needed to load above jdbc URL (optional)
#
# sldg.hash.jdbc.driver.classpath:
#  Path to .jar bundle containing the named driver class (optional)
#
# sldg.hash.table.prefix:
#  Hash-ledger tables (3) use this prefix in their table names. Usually set to
#  the source table's name.
#
# The following 3 specify the SQL schemas for the hash tables. They may be
# DB vendor specific.
#
# sldg.hash.schema.skip:
#  SQL schema (CREATE TABLE statement) for the skipledger table (defaulted)
#
# sldg.hash.schema.chain:
#  SQL schema (CREATE TABLE statement) for the chain table (defaulted)
#
# sldg.hash.schema.trail:
#  SQL schema (CREATE TABLE statement) for the trail table (defaulted)
#
# Note, driver classpaths above may either be set absolutely, or relative to
# the location of this file.
#
#
#Wed Sep 29 22:15:14 MDT 2021
sldg.source.jdbc.url=jdbc\:sqlite\:/Users/babak/code/workspace/ledgers/sandbox/sqlite_sample/chinook.db
sldg.source.jdbc.driver=org.sqlite.JDBC
sldg.source.jdbc.driver.classpath=../sqlite_sample/sqlite-jdbc-3.36.0.2.jar
sldg.source.query.size=SELECT count(*) FROM invoice_items AS rcount
sldg.source.query.row=SELECT * FROM (  SELECT ROW_NUMBER() OVER (ORDER BY InvoiceLineId ASC) AS row_index, InvoiceLineId, invoice_items.InvoiceId, TrackId, UnitPrice, Quantity, invoices.CustomerId, invoices.InvoiceDate, invoices.BillingAddress, invoices.BillingCity, invoices.BillingState, invoices.BillingCountry, invoices.BillingPostalCode, invoices.Total FROM invoice_items INNER JOIN invoices ON invoices.InvoiceId = invoice_items.InvoiceId) AS snap WHERE row_index \= ?
#
# Replace RHS value below w/ random 64 digit hex value: eg the SHA-256 of some random file
#
sldg.source.salt.seed=06a3861355760acb05fc1607c6786b828c8e98c4f4698af9324967a208346
sldg.hash.table.prefix=invoice_items
sldg.hash.schema.skip=CREATE TABLE invoice_items_sldg (   row_num BIGINT NOT NULL,  src_hash CHAR(43) NOT NULL,  row_hash CHAR(43) NOT NULL,  PRIMARY KEY (row_num) )
sldg.hash.schema.trail=CREATE TABLE invoice_items_sldg_tr (  trl_id INT NOT NULL,  row_num BIGINT NOT NULL,  utc BIGINT NOT NULL,  mrkl_idx INT NOT NULL,  mrkl_cnt INT NOT NULL,  chain_len INT NOT NULL,  chn_id INT NOT NULL,  PRIMARY KEY (trl_id),  FOREIGN KEY (row_num) REFERENCES invoice_items_sldg(row_num),  FOREIGN KEY (chn_id) REFERENCES invoice_items_sldg_ch(chn_id) )
sldg.hash.schema.chain=CREATE TABLE invoice_items_sldg_ch (  chn_id INT NOT NULL,  n_hash CHAR(43) NOT NULL,  PRIMARY KEY (chn_id)  )
sldg.meta.path=meta/chinook_info.json
sldg.template.report.path=report