src/main/java/com/conveyal/gtfs/loader/JdbcGTFSFeedConverter.java
public FeedLoadResult loadTables () {

        // This result object will be returned to the caller to summarize the feed and report any critical errors.
        FeedLoadResult result = new FeedLoadResult();

        try {
            // Begin tracking time. FIXME: should this follow the connect/register and begin with the table loads?
            long startTime = System.currentTimeMillis();
            // We get a single connection object and share it across several different methods.
            // This ensures that actions taken in one method are visible to all subsequent SQL statements.
            // If we create a schema or table on one connection, then access it in a separate connection, we have no
            // guarantee that it exists when the accessing statement is executed.
            connection = dataSource.getConnection();
            // Generate a unique prefix that will identify this feed.
            // Prefixes ("schema" names) based on feed_id and feed_version get very messy, so we use random unique IDs.
            // We don't want to use an auto-increment numeric primary key because these need to be alphabetical.
            // Although ID collisions are theoretically possible, they are improbable in the extreme because our IDs
            // are long enough to have as much entropy as a UUID. So we don't really need to check for uniqueness and
            // retry in a loop.
            // TODO handle the case where we don't want any prefix.
            this.tablePrefix = this.namespace = randomIdString();
            result.uniqueIdentifier = tablePrefix;
            registerFeed();
            // Include the dot separator in the table prefix.
            // This allows everything to work even when there's no prefix.
            this.tablePrefix += ".";
            this.errorStorage = new SQLErrorStorage(connection, tablePrefix, true);

            // Get entity lists that are nested in feed.
            List<Calendar> calendars = gtfsFeed.services.values()
                    .stream()
                    .map(service -> service.calendar)
                    .collect(Collectors.toList());
            List<CalendarDate> calendarDates = gtfsFeed.services.values()
                    .stream()
                    .map(service -> service.calendar_dates.values())
                    .flatMap(Collection::stream)
                    .collect(Collectors.toList());
            List<FareAttribute> fareAttributes = gtfsFeed.fares.values()
                    .stream()
                    .map(fare -> fare.fare_attribute)
                    .collect(Collectors.toList());
            List<FareRule> fareRules = gtfsFeed.fares.values()
                    .stream()
                    .map(fare -> fare.fare_rules)
                    .flatMap(List::stream)
                    .collect(Collectors.toList());
            List<Frequency> frequencies = gtfsFeed.frequencies.stream()
                    .map(stringFrequencyTuple2 -> stringFrequencyTuple2.b)
                    .collect(Collectors.toList());

            // Copy all tables (except for PATTERN_STOPS, which does not exist in GTFSFeed).
            copyEntityToSql(gtfsFeed.agency.values(), Table.AGENCY);
            copyEntityToSql(calendars, Table.CALENDAR);
            copyEntityToSql(calendarDates, Table.CALENDAR_DATES);
            copyEntityToSql(gtfsFeed.routes.values(), Table.ROUTES);
            copyEntityToSql(gtfsFeed.patterns.values(), Table.PATTERNS);
            // FIXME: How to handle pattern stops?
//            copyEntityToSql(gtfsFeed.patterns.values(), Table.PATTERN_STOP);
            copyEntityToSql(fareAttributes, Table.FARE_ATTRIBUTES);
            copyEntityToSql(fareRules, Table.FARE_RULES);
            copyEntityToSql(gtfsFeed.feedInfo.values(), Table.FEED_INFO);
            copyEntityToSql(gtfsFeed.shape_points.values(), Table.SHAPES);
            copyEntityToSql(gtfsFeed.stops.values(), Table.STOPS);
            copyEntityToSql(gtfsFeed.transfers.values(), Table.TRANSFERS);
            copyEntityToSql(gtfsFeed.trips.values(), Table.TRIPS); // refs routes
            copyEntityToSql(frequencies, Table.FREQUENCIES); // refs trips
            copyEntityToSql(gtfsFeed.stop_times.values(), Table.STOP_TIMES);
//            result.errorCount = errorStorage.getErrorCount();
            // This will commit and close the single connection that has been shared between all preceding load steps.
            errorStorage.commitAndClose();
            result.completionTime = System.currentTimeMillis();
            result.loadTimeMillis = result.completionTime - startTime;
            LOG.info("Loading tables took {} sec", result.loadTimeMillis / 1000);
        } catch (Exception ex) {
            try {
                connection.rollback();
            } catch (SQLException e) {
                e.printStackTrace();
            }
            // TODO catch exceptions separately while loading each table so load can continue, store in TableLoadResult
            LOG.error("Exception while loading GTFS file: {}", ex.toString());
            ex.printStackTrace();
            result.fatalException = ex.getMessage();
        } finally {
            DbUtils.closeQuietly(connection);
        }
        return result;
    }
public FeedLoadResult loadTables () {

        // This result object will be returned to the caller to summarize the feed and report any critical errors.
        FeedLoadResult result = new FeedLoadResult();

        try {
            // Begin tracking time. FIXME: should this follow the connect/register and begin with the table loads?
            long startTime = System.currentTimeMillis();
            // We get a single connection object and share it across several different methods.
            // This ensures that actions taken in one method are visible to all subsequent SQL statements.
            // If we create a schema or table on one connection, then access it in a separate connection, we have no
            // guarantee that it exists when the accessing statement is executed.
            connection = dataSource.getConnection();
            // Generate a unique prefix that will identify this feed.
            // Prefixes ("schema" names) based on feed_id and feed_version get very messy, so we use random unique IDs.
            // We don't want to use an auto-increment numeric primary key because these need to be alphabetical.
            // Although ID collisions are theoretically possible, they are improbable in the extreme because our IDs
            // are long enough to have as much entropy as a UUID. So we don't really need to check for uniqueness and
            // retry in a loop.
            // TODO handle the case where we don't want any prefix.
            this.tablePrefix = this.namespace = randomIdString();
            result.uniqueIdentifier = tablePrefix;
            registerFeed();
            // Include the dot separator in the table prefix.
            // This allows everything to work even when there's no prefix.
            this.tablePrefix += ".";
            this.errorStorage = new SQLErrorStorage(connection, tablePrefix, true);

            // Get entity lists that are nested in feed.
            List<Calendar> calendars = gtfsFeed.services.values()
                    .stream()
                    .map(service -> service.calendar)
                    .collect(Collectors.toList());
            List<CalendarDate> calendarDates = gtfsFeed.services.values()
                    .stream()
                    .map(service -> service.calendar_dates.values())
                    .flatMap(Collection::stream)
                    .collect(Collectors.toList());
            List<FareAttribute> fareAttributes = gtfsFeed.fares.values()
                    .stream()
                    .map(fare -> fare.fare_attribute)
                    .collect(Collectors.toList());
            List<FareRule> fareRules = gtfsFeed.fares.values()
                    .stream()
                    .map(fare -> fare.fare_rules)
                    .flatMap(List::stream)
                    .collect(Collectors.toList());
            List<Frequency> frequencies = gtfsFeed.frequencies.stream()
                    .map(stringFrequencyTuple2 -> stringFrequencyTuple2.b)
                    .collect(Collectors.toList());

            // Copy all tables (except for PATTERN_STOPS, which does not exist in GTFSFeed).
            copyEntityToSql(gtfsFeed.agency.values(), Table.AGENCY);
            copyEntityToSql(calendars, Table.CALENDAR);
            copyEntityToSql(calendarDates, Table.CALENDAR_DATES);
            copyEntityToSql(gtfsFeed.routes.values(), Table.ROUTES);
            copyEntityToSql(gtfsFeed.patterns.values(), Table.PATTERNS);
            // FIXME: How to handle pattern stops?
//            copyEntityToSql(gtfsFeed.patterns.values(), Table.PATTERN_STOP);
            copyEntityToSql(fareAttributes, Table.FARE_ATTRIBUTES);
            copyEntityToSql(fareRules, Table.FARE_RULES);
            copyEntityToSql(gtfsFeed.feedInfo.values(), Table.FEED_INFO);
            copyEntityToSql(gtfsFeed.shape_points.values(), Table.SHAPES);
            copyEntityToSql(gtfsFeed.stops.values(), Table.STOPS);
            copyEntityToSql(gtfsFeed.transfers.values(), Table.TRANSFERS);
            copyEntityToSql(gtfsFeed.trips.values(), Table.TRIPS); // refs routes
            copyEntityToSql(frequencies, Table.FREQUENCIES); // refs trips
            copyEntityToSql(gtfsFeed.stop_times.values(), Table.STOP_TIMES);
//            result.errorCount = errorStorage.getErrorCount();
            // This will commit and close the single connection that has been shared between all preceding load steps.
            errorStorage.commitAndClose();
            result.completionTime = System.currentTimeMillis();
            result.loadTimeMillis = result.completionTime - startTime;
            LOG.info("Loading tables took {} sec", result.loadTimeMillis / 1000);
        } catch (Exception ex) {
            try {
                connection.rollback();
            } catch (SQLException e) {
                e.printStackTrace();
            }
            // TODO catch exceptions separately while loading each table so load can continue, store in TableLoadResult
            LOG.error("Exception while loading GTFS file: {}", ex.toString());
            ex.printStackTrace();
            result.fatalException = ex.getMessage();
        } finally {
            DbUtils.closeQuietly(connection);
        }
        return result;
    }
There appears to be no advantage to loading tables in parallel, as the whole loading process is I/O bound.